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coursera-course-dataset

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R Programming

Johns Hopkins University

Computational Thinking, Computer Programming, Computer Programming Tools, Critical Thinking, Data Analysis, Data Structures, Problem Solving, Programming Principles, R Programming, Statistical Programming, General Statistics

22K

Intermediate

Course

1 - 4 Weeks

Understanding Medical Research: Your Facebook Friend is Wrong

Yale University

General Statistics

1.8K

Beginner

Course

1 - 3 Months

Essential Causal Inference Techniques for Data Science

Coursera Project Network

Regression

33

Beginner

Guided Project

Less Than 2 Hours

Computational Neuroscience

University of Washington

Mathematics, Computer Programming, Mathematical Theory & Analysis, Probability & Statistics, Python Programming, Computational Logic, Data Analysis, Artificial Neural Networks, Linear Algebra, Machine Learning, Human Learning

https://www.coursera.org/learn/computational-neuroscience

Embark on an exciting journey into the world of cybersecurity with this comprehensive specialization. Designed for beginners, this cybersecurity specialization provides an introduction to cybersecurity, including basic knowledge and key skills needed to confidently start training for CompTIA Security+ certification. In today's digital age, cybersecurity professionals are in high demand and are one of the highest-paying IT career paths. Job opportunities in this fast-growing sector seek applicants with technical skills, analytical thinking and creative problem-solving qualifications. Through this specialization, you'll learn from cybersecurity experts and industry insiders about the day-to-day tasks and challenges you can expect in this role. You'll gain insights into how to protect a company's valuable information from theft and damage, ensuring that computers and networks store and process data according to the organization’s rules. Moreover, you'll acquire practical computer and network administration skills, preparing you to confidently begin a complete cybersecurity training program. This is your first step to becoming a key player in the cybersecurity field. Don't miss this opportunity to kickstart your career in cybersecurity. Enroll in this specialization today and take the first step towards a promising future in information security. Applied Learning Project In this cybersecurity specialization, you'll engage in practical activities that serve as a steppingstone to meet the pre-requisites for Security+ training. You'll gain hands-on experience in securing Windows and Linux systems, networking and scripting. You'll be able to test your knowledge through multiple-choice practice questions with extensive feedback. Additionally, you'll have access to informative videos and interviews with seasoned industry professionals, providing real-world context and insights into how these skills are applied in the cybersecurity field. This course is designed with accessibility in mind, meeting WCAG 2.0 AA compliance, including keyboard navigation, alt-tags for images, captions for videos, screen reader compatibility and adherence to color contrast guidelines. 

1K

Beginner

Course

1 - 3 Months

The Arts and Science of Relationships: Understanding Human Needs

University of Toronto

Emotional Intelligence, Communication

https://www.coursera.org/learn/human-needs

206,340

This course provides an introduction to: 1. Basic concepts of The Strategies and Skills Learning and Development System (SSLD), their relevance for every day relationships and provide advanced concepts for participants who work in fields of social work and health care . 2. Basic practice principles and methods of SSLD, illustrated by relationship management case studies. 3. The SSLD framework for relationship management assessment; N3C (needs, circumstances, characteristics, capacity) and problem translation. 4. Core competencies in the relationship management application of the SSLD system: Observation learning, simulation, real life implementation, review and monitoring.

1.6K

Beginner

Course

1 - 3 Months

Analytics for Decision Making

University of Minnesota

Data Analysis, Decision Making, Business Analysis, Statistical Analysis, Probability & Statistics, General Statistics, Mathematics, Spreadsheet Software, Mathematical Theory & Analysis, Algebra, Forecasting, Linear Algebra, Microsoft Excel, Plot (Graphics), Probability Distribution, Regression, Leadership and Management, Statistical Machine Learning, Basic Descriptive Statistics, Generally Accepted Accounting Principles (GAAP), Strategy and Operations, Operations Management

182

Beginner

Specialization

3 - 6 Months

Narrative Economics

Yale University

Critical Thinking, Storytelling

https://www.coursera.org/learn/narrative-economics

44,895

This Specialization will give you the knowledge and tools you need to record and produce professional sounding music. You will begin by developing your identity, vision, and intention as an artist and producer. Next, you will learn the technical aspects of music production, including how sound is translated into audio signals, recording techniques, and effects such as reverb, delay, and compression. You will also learn how to use the industry standard Digital Audio Workstation, Pro Tools, to create professional recordings. Finally, you will apply the knowledge and tools you gained in a culminating 4-week Capstone where you will complete a project beginning at the pre-production stage through the recording, mixing, and mastering stages.

370

Beginner

Course

1 - 4 Weeks

Julia Scientific Programming

University of Cape Town

Computer Programming, Mathematics, Other Programming Languages, Computational Thinking, Data Visualization, Programming Principles

425

Beginner

Course

1 - 4 Weeks

Introduction to Artificial Intelligence (AI)

IBM

Algorithms, Applied Machine Learning, Artificial Neural Networks, Computer Vision, Deep Learning, Human Learning, Machine Learning, Machine Learning Algorithms, Machine Learning Software, Big Data, Data Science

https://www.coursera.org/learn/introduction-to-ai

47,937

Get started with using Agile Development and Scrum with this self-paced introductory course! After successfully completing this course, you will be able to embrace the Agile concepts of adaptive planning, iterative development, and continuous improvement - resulting in early deliveries and value to customers. You will look at Scrum as a framework and learn how to apply it alongside Agile. You will also become familiar with related methodologies like Waterfall, Extreme Programming (XP), and Kanban. Apply Agile practices derived from lean manufacturing concepts, like test-driven development. Learn how a scrum team functions. Also learn about the importance of Agile iterative planning and enable yourself to write good user stories and track your team’s progress using a kanban board. Create and refine a product backlog collaboratively with the team and the customer, in a flexible and blameless culture. You'll also learn how to use burndown charts, achieve sprint goals, and conduct the sprint review and retrospective. This approach will lead you to higher levels of efficiency, with the ability to plan and execute sprints with your development team, measuring success with actionable metrics. This course is about more than facts and processes. It is about working collaboratively on a self-organizing team, coached by a scrum master, and building what is needed, rather than simply following a plan. Developed and taught by an experienced Agile practitioner, the course includes hands-on practice through realistic scenario-based labs using GitHub and ZenHub. The course will benefit anyone who wants to get started with working the Agile way or transform the organizational culture to adopt and realize the benefits of Scrum. This includes Project Managers, Product Managers, and Executives. It is particularly suitable for IT practitioners such as software developers, development managers, and IT Scrum Masters.

12K

Beginner

Course

1 - 4 Weeks

NLP: Twitter Sentiment Analysis

Coursera Project Network

Machine Learning, Natural Language Processing, Python Programming

350

Beginner

Guided Project

Less Than 2 Hours

Ciclo completo del desarrollo de un proyecto de Data Science

Coursera Project Network

Machine Learning

32

Beginner

Guided Project

Less Than 2 Hours

Statistical Inference for Estimation in Data Science

University of Colorado Boulder

General Statistics, Probability & Statistics, Probability Distribution, Estimation, Calculus, Statistical Tests

53

Intermediate

Course

1 - 3 Months

Sequences, Time Series and Prediction

DeepLearning.AI

Machine Learning, Forecasting, Tensorflow, Applied Machine Learning, Deep Learning, Artificial Neural Networks, Human Learning, Data Visualization, Machine Learning Algorithms, Statistical Analysis

https://www.coursera.org/learn/tensorflow-sequences-time-series-and-prediction

125,323

If you are a software developer who wants to build scalable AI-powered algorithms, you need to understand how to use the tools to build them. This Specialization will teach you best practices for using TensorFlow, a popular open-source framework for machine learning. In this fourth course, you will learn how to build time series models in TensorFlow. You’ll first implement best practices to prepare time series data. You’ll also explore how RNNs and 1D ConvNets can be used for prediction. Finally, you’ll apply everything you’ve learned throughout the Specialization to build a sunspot prediction model using real-world data! The Machine Learning course and Deep Learning Specialization from Andrew Ng teach the most important and foundational principles of Machine Learning and Deep Learning. This new deeplearning.ai TensorFlow Specialization teaches you how to use TensorFlow to implement those principles so that you can start building and applying scalable models to real-world problems. To develop a deeper understanding of how neural networks work, we recommend that you take the Deep Learning Specialization.

4.9K

Intermediate

Course

1 - 4 Weeks

Introduction to Relational Database and SQL

Coursera Project Network

Databases, SQL, Data Science, Leadership and Management

1.8K

Beginner

Guided Project

Less Than 2 Hours

Data Processing Using Python

Nanjing University

Computer Programming, Python Programming, Data Analysis, Programming Principles, Data Structures, Mathematical Theory & Analysis, Statistical Programming

339

Beginner

Course

1 - 3 Months

MLOps | Machine Learning Operations

Duke University

Applied Machine Learning, Big Data, Cloud Computing, Computer Programming, DevOps, Machine Learning, Machine Learning Software, Microsoft Azure, Python Programming

https://www.coursera.org/specializations/mlops-machine-learning-duke

5,105

This comprehensive course series is perfect for individuals with programming knowledge such as software developers, data scientists, and researchers. You'll acquire critical MLOps skills, including the use of Python and Rust, utilizing GitHub Copilot to enhance productivity, and leveraging platforms like Amazon SageMaker, Azure ML, and MLflow. You'll also learn how to fine-tune Large Language Models (LLMs) using Hugging Face and understand the deployment of sustainable and efficient binary embedded models in the ONNX format, setting you up for success in the ever-evolving field of MLOps Through this series, you will begin to learn skills for various career paths: 1. Data Science - Analyze and interpret complex data sets, develop ML models, implement data management, and drive data-driven decision making. 2. Machine Learning Engineering - Design, build, and deploy ML models and systems to solve real-world problems. 3. Cloud ML Solutions Architect - Leverage cloud platforms like AWS and Azure to architect and manage ML solutions in a scalable, cost-effective manner. 4. Artificial Intelligence (AI) Product Management - Bridge the gap between business, engineering, and data science teams to deliver impactful AI/ML products. Applied Learning Project Explore and practice your MLOps skills with hands-on practice exercises and Github repositories. 1. Building a Python script to automate data preprocessing and feature extraction for machine learning models. 2. Developing a real-world ML/AI solution using AI pair programming and GitHub Copilot, showcasing your ability to collaborate with AI. 4. Creating web applications and command-line tools for ML model interaction using Gradio, Hugging Face, and the Click framework. 3. Implementing GPU-accelerated ML tasks using Rust for improved performance and efficiency. 4. Training, optimizing, and deploying ML models on Amazon SageMaker and Azure ML for cloud-based MLOps. 5. Designing a full MLOps pipeline with MLflow, managing projects, models, and tracking system features. 6. Fine-tuning and deploying Large Language Models (LLMs) and containerized models using the ONNX format with Hugging Face. Creating interactive demos to effectively showcase your work and advancements.

150

Advanced

Specialization

3 - 6 Months

Perform data science with Azure Databricks

Microsoft

Microsoft Azure, Big Data, Cloud Computing, Machine Learning, Applied Machine Learning, Cloud Applications, Data Management, Extract, Transform, Load, Python Programming, Cloud Storage

44

Intermediate

Course

1 - 3 Months

Data Analysis with SQL: Inform a Business Decision

Coursera Project Network

Data Analysis, SQL

22

Beginner

Guided Project

Less Than 2 Hours

Python Packages for Data Science

University of Colorado Boulder

Python Programming, Data Visualization

24

Intermediate

Course

1 - 4 Weeks

Econometrics: Methods and Applications

Erasmus University Rotterdam

Econometrics, General Statistics, Regression

1.2K

Mixed

Course

1 - 3 Months

Understanding and Visualizing Data with Python

University of Michigan

Basic Descriptive Statistics, Data Analysis, General Statistics, Probability & Statistics, Statistical Analysis, Probability Distribution, Statistical Visualization, Data Visualization, Python Programming, Statistical Programming, Computer Programming

2.6K

Beginner

Course

1 - 4 Weeks

Data Visualization with Advanced Excel

PwC

Business Analysis, Data Analysis, Data Analysis Software, Data Model, Data Visualization, Microsoft Excel, Spreadsheet Software, Data Management, Data Visualization Software, Interactive Data Visualization

2.9K

Beginner

Course

1 - 4 Weeks

Statistical Inference and Hypothesis Testing in Data Science Applications

University of Colorado Boulder

General Statistics, Probability & Statistics, Statistical Tests

31

Intermediate

Course

1 - 3 Months

An Intuitive Introduction to Probability

University of Zurich

Probability & Statistics, Probability Distribution, General Statistics

1.6K

Beginner

Course

1 - 3 Months

Data Collection and Processing with Python

University of Michigan

Computer Programming, Python Programming

3.8K

Intermediate

Course

1 - 4 Weeks

Prepare Data for Exploration

Google

Data Management, Data Analysis, Databases, Microsoft Excel, SQL, Spreadsheet Software

https://www.coursera.org/learn/data-preparation

645,914

This is the third course in the Google Data Analytics Certificate. These courses will equip you with the skills needed to apply to introductory-level data analyst jobs. As you continue to build on your understanding of the topics from the first two courses, you’ll also be introduced to new topics that will help you gain practical data analytics skills. You’ll learn how to use tools like spreadsheets and SQL to extract and make use of the right data for your objectives and how to organize and protect your data. Current Google data analysts will continue to instruct and provide you with hands-on ways to accomplish common data analyst tasks with the best tools and resources. Learners who complete this certificate program will be equipped to apply for introductory-level jobs as data analysts. No previous experience is necessary. By the end of this course, you will: - Find out how analysts decide which data to collect for analysis. - Learn about structured and unstructured data, data types, and data formats. - Discover how to identify different types of bias in data to help ensure data credibility. - Explore how analysts use spreadsheets and SQL with databases and data sets. - Examine open data and the relationship between and importance of data ethics and data privacy. - Gain an understanding of how to access databases and extract, filter, and sort the data they contain. - Learn the best practices for organizing data and keeping it secure.

18K

Beginner

Course

1 - 3 Months

Introduction to Microsoft Excel

Coursera Project Network

Data Analysis, Microsoft Excel, Data Management, Leadership and Management

4.5K

Intermediate

Guided Project

Less Than 2 Hours

Python Project for Data Engineering

IBM

Computer Programming, Data Management, Data Mining, Data Structures, Extract, Transform, Load, Python Programming

https://www.coursera.org/learn/python-project-for-data-engineering

32,522

Showcase your Python skills in this Data Engineering Project! This short course is designed to apply your basic Python skills through the implementation of various techniques for gathering and manipulating data. You will take on the role of a Data Engineer by extracting data from multiple sources, and converting the data into specific formats and making it ready for loading into a database for analysis. You will also demonstrate your knowledge of web scraping and utilizing APIs to extract data. By the end of this hands-on project, you will have shown your proficiency with important skills to Extract Transform and Load (ETL) data using an IDE, and of course, Python Programming. Upon completion of this course, you will also have a great new addition to your portfolio! PRE-REQUISITE: **Python for Data Science, AI and Development** course from IBM is a pre-requisite for this project course. Please ensure that before taking this course you have either completed the Python for Data Science, AI and Development course from IBM or have equivalent proficiency in working with Python and data. NOTE: This course is not intended to teach you Python and does not have too much new instructional content. It is intended for you to mostly apply prior Python knowledge.

532

Intermediate

Course

1 - 4 Weeks

Practical Data Science with MATLAB

MathWorks

Data Analysis, Exploratory Data Analysis, Matlab, Machine Learning, Data Visualization, Data Analysis Software, Interactive Data Visualization, Probability & Statistics, Statistical Visualization, Applied Machine Learning, Machine Learning Algorithms, Regression, Data Visualization Software, Plot (Graphics), Statistical Analysis, Machine Learning Software, Training, Correlation And Dependence, Data Structures, Feature Engineering, Data Science

https://www.coursera.org/specializations/practical-data-science-matlab

19,450

Development environments might not have the exact requirements as production environments. Moving data science and machine learning projects from idea to production requires state-of-the-art skills. You need to architect and implement your projects for scale and operational efficiency. Data science is an interdisciplinary field that combines domain knowledge with mathematics, statistics, data visualization, and programming skills. The Practical Data Science Specialization brings together these disciplines using purpose-built ML tools in the AWS cloud. It helps you develop the practical skills to effectively deploy your data science projects and overcome challenges at each step of the ML workflow using Amazon SageMaker. This Specialization is designed for data-focused developers, scientists, and analysts familiar with the Python and SQL programming languages who want to learn how to build, train, and deploy scalable, end-to-end ML pipelines - both automated and human-in-the-loop - in the AWS cloud. Each of the 10 weeks features a comprehensive lab developed specifically for this Specialization that provides hands-on experience with state-of-the-art algorithms for natural language processing (NLP) and natural language understanding (NLU), including BERT and FastText using Amazon SageMaker. Applied Learning Project By the end of this Specialization, you will be ready to: • Ingest, register, and explore datasets • Detect statistical bias in a dataset • Automatically train and select models with AutoML • Create machine learning features from raw data • Save and manage features in a feature store • Train and evaluate models using built-in algorithms and custom BERT models • Debug, profile, and compare models to improve performance • Build and run a complete ML pipeline end-to-end • Optimize model performance using hyperparameter tuning • Deploy and monitor models • Perform data labeling at scale • Build a human-in-the-loop pipeline to improve model performance • Reduce cost and improve performance of data products

1K

Beginner

Specialization

3 - 6 Months

IBM Data Analyst Capstone Project

IBM

Python Programming, Exploratory Data Analysis, Computer Programming, Data Analysis, Data Visualization, Microsoft Excel, SQL

1K

Intermediate

Course

1 - 3 Months

Spark, Hadoop, and Snowflake for Data Engineering

Duke University

Big Data, Data Warehousing, Python Programming

https://www.coursera.org/learn/spark-hadoop-snowflake-data-engineering

e.g. This is primarily aimed at first- and second-year undergraduates interested in engineering or science, along with high school students and professionals with an interest in programmingGain the skills for building efficient and scalable data pipelines. Explore essential data engineering platforms (Hadoop, Spark, and Snowflake) as well as learn how to optimize and manage them. Delve into Databricks, a powerful platform for executing data analytics and machine learning tasks, while honing your Python data science skills with PySpark. Finally, discover the key concepts of MLflow, an open-source platform for managing the end-to-end machine learning lifecycle, and learn how to integrate it with Databricks. This course is designed for learners who want to pursue or advance their career in data science or data engineering, or for software developers or engineers who want to grow their data management skill set. In addition to the technologies you will learn, you will also gain methodologies to help you hone your project management and workflow skills for data engineering, including applying Kaizen, DevOps, and Data Ops methodologies and best practices. With quizzes to test your knowledge throughout, this comprehensive course will help guide your learning journey to become a proficient data engineer, ready to tackle the challenges of today's data-driven world.

6

Advanced

Course

1 - 4 Weeks

Cloud Computing

University of Illinois at Urbana-Champaign

Cloud Computing, Distributed Computing Architecture, Cloud Infrastructure, Computer Networking, Cloud Storage, Cloud Platforms, Network Architecture, Apache, Cloud Applications, Cloud Engineering, Computer Architecture, Data Management, Algorithms, Software-Defined Networking, Software As A Service, Network Analysis, Theoretical Computer Science, Amazon Web Services, Big Data, Cloud-Based Integration, Software Architecture, Computational Thinking, Computer Programming, Cryptography, Security Engineering, Human Learning, Python Programming

2K

Intermediate

Specialization

3 - 6 Months

Leverage Data Science for a More Agile Supply Chain

University of California, Irvine

Inventory Management, Data Analysis, Supply Chain Systems, Leadership and Management, Business Analysis, Forecasting, Supply Chain and Logistics

https://www.coursera.org/specializations/leverage-data-science-agile-supply-chain

4,041

Over the past two decades, the supply chain has become more complex. While advancing technology has allowed companies to capture this complexity within stores of ever accumulating data, companies have not kept up with how to analyze and derive insights from that data. This specialization uses hands-on activities to show how data science techniques can turn raw data into decision-makers for a more agile supply chain. Foundational techniques such as demand forecasting, inventory management with demand variability, and using the newsvendor model are covered, in addition to more advanced techniques such as how to optimize for capacity and resources as well as mitigate risks with the Monte Carlo simulation. By the end of this specialization, you will be able to: Describe how demand planning, supply planning, and constrained forecast are associated with one another. Use Excel to analyze historical data to quantify future needs. Analyze historical data to determine inventory levels in steady and uncertain demand situations using Excel. Manage inventory in an uncertain environment. Quantify the inventory needs for single-period items using the newsvendor model. Identify the components of capacity optimization, resource optimization, and Monte Carlo simulation. Set up and solve optimization problems in Excel. Build a demand and inventory snapshot and run a Monte Carlo simulation to solve for a more agile supply chain. Applied Learning Project Throughout the specialization, learners work with real-world supply chain data to analyze various supply chain scenarios. To close, learners apply concepts from all three courses to apply learned data science skills to improve the margins of a supply chain.

182

Intermediate

Specialization

1 - 3 Months

Essential Linear Algebra for Data Science

University of Colorado Boulder

Algebra, Linear Algebra, Mathematics

124

Intermediate

Course

1 - 3 Months

SQL for Data Science Capstone Project

University of California, Davis

Data Analysis, Data Model, Exploratory Data Analysis, SQL

215

Intermediate

Course

1 - 4 Weeks

Spatial Data Science and Applications

Yonsei University

Data Analysis, Spatial Analysis, Spatial Data Analysis, Big Data, Data Visualization, Databases, Geovisualization, Data Management, Data Model, Data Visualization Software

485

Intermediate

Course

1 - 3 Months

Command Line Tools for Genomic Data Science

Johns Hopkins University

Bioinformatics, Computer Programming, Data Analysis, Computer Programming Tools, Data Analysis Software, Exploratory Data Analysis, Operating Systems, Computational Thinking, Programming Principles, Problem Solving

540

Mixed

Course

1 - 4 Weeks

Statistics for Genomic Data Science

Johns Hopkins University

Bioinformatics, General Statistics, R Programming, Statistical Analysis, Statistical Tests, Biostatistics, Data Analysis, Probability & Statistics, Correlation And Dependence, Statistical Programming

350

Mixed

Course

1 - 4 Weeks

Integral Calculus and Numerical Analysis for Data Science

University of Colorado Boulder

Calculus, Mathematics, Mathematical Theory & Analysis

75

Intermediate

Course

1 - 4 Weeks

Advanced Linear Models for Data Science 1: Least Squares

Johns Hopkins University

General Statistics, Probability & Statistics, Linear Algebra, Mathematics, Regression, Algebra, Correlation And Dependence

184

Advanced

Course

1 - 3 Months

Prepare for DP-100: Data Science on Microsoft Azure Exam

Microsoft

Machine Learning, Microsoft Azure, Machine Learning Algorithms, Algorithms, Applied Machine Learning, Data Analysis, Human Learning, Machine Learning Software, Python Programming

35

Intermediate

Course

1 - 3 Months

Executive Data Science Capstone

Johns Hopkins University

Data Analysis, Data Management, Leadership and Management

1.5K

Mixed

Course

1 - 4 Weeks

Advanced Linear Models for Data Science 2: Statistical Linear Models

Johns Hopkins University

General Statistics, Probability & Statistics, Linear Algebra, Mathematics, Algebra, Regression

92

Advanced

Course

1 - 4 Weeks

Data Science Fundamentals for Data Analysts

Databricks

Data Analysis, Data Science, Machine Learning

51

Intermediate

Course

1 - 3 Months

Data Science Project: MATLAB for the Real World

MathWorks

Data Analysis, Machine Learning, Data Science, Matlab

24

Intermediate

Course

1 - 4 Weeks

Data Science Capstone

Johns Hopkins University

Data Analysis, Natural Language Processing, R Programming, Exploratory Data Analysis, Human Learning, Machine Learning, Machine Learning Algorithms, Problem Solving, Statistical Machine Learning, Computer Programming

1.2K

Mixed

Course

1 - 3 Months

Introduction to Networking and Storage

IBM

Computer Networking, Cloud Storage, Networking Hardware, Cloud Computing, Network Architecture

311

Beginner

Course

1 - 3 Months

Networking Fundamentals

Akamai Technologies, Inc.

Network Architecture, Network Security

11

Beginner

Course

1 - 3 Months

Computer Communications

University of Colorado System

Computer Networking, Network Model, Network Security, Network Architecture, Networking Hardware, Communication, Computer Architecture, Network Analysis, Theoretical Computer Science, Account Management, Software-Defined Networking, Leadership and Management, Back-End Web Development, Computer Graphics, Internet Of Things, Operational Analysis, Scrum (Software Development), Visualization (Computer Graphics), Accounts Payable and Receivable, Algorithms, Organizational Development

3.1K

Intermediate

Specialization

3 - 6 Months

Network Automation Engineering Fundamentals

Cisco Learning and Certifications

DevOps, Python Programming

https://www.coursera.org/specializations/networkautomation

6,285

In this course, you will learn crucial skills needed to understand the intricate dynamics that go into the process of negotiation, and how you can go into your negotiation confident and fully prepared. You'll learn about the framework that goes into shaping a successful negotiation, in addition to gaining the knowledge that will allow you to adapt to rapidly changing circumstances. You'll also learn about emotional control, crafting questions to help you get the information that you need, and skills that will allow you to negotiate in any setting. You will also successfully learn how to navigate a negotiation through real-world exercises, and how to best work to build trust, diffuse anger, and make rational decisions based on the information at hand. Lastly, you will learn how to prepare to negotiate in any setting and use your skills to facilitate with teams and influence outcomes. By the end of this course, you’ll be able to utilize your newly acquired skills to successfully negotiate for employment, contracts, and in any part of your life. Within this course, you will end with the knowledge of how to craft a successful negotiation strategy and manage the conflict that can arise, as well as build trust.

34

Beginner

Specialization

3 - 6 Months

Akamai Network Engineering

Akamai Technologies, Inc.

Computer Security Incident Management, Mobile Security, Network Architecture, Network Security, Risk Management

https://www.coursera.org/professional-certificates/akamai-network-engineering

2,214

Are you interested in learning how large global network operations work?  Does managing  30% of the internet traffic globally intrigue you? Then the Network Engineering certification is for you. The NOCC is a proactive monitoring and troubleshooting team that monitors and manages globally distributed servers and resolves network bottlenecks in real time.  This beginner level certificate is designed to provide you with in-demand skills that range from internet technology fundamentals, networking, operating systems and problem solving techniques.  This certificate program consists of 5-courses, developed by Akamai, that are self-paced and can be completed over 5-months. The courses will help you build solid technical foundations and troubleshooting skills that align to entry level jobs in the Network Engineering field. Target Jobs: Network Engineering & Network Operations Support Roles Applied Learning Project Students will build and secure a Linux virtual machine using virtualization technology. They will also create complex networks using Cisco Packet Tracer, implementing routing, NAT, port forwarding, DHCP, DNS, and packet sniffers. As well as troubleshooting and resolving complex network problems. Students will design a relational database to contain customer data and security incidents and create queries to analyze the data. Then, after creating four Python applications from scratch: an age calculator, a word guessing game, a lemonade stand game, and a text-based adventure game, students will create the code to connect a web site to the database to authenticate users and provide user-specific content to users after login.

35

Beginner

Professional Certificate

3 - 6 Months

Cybersecurity Operations Fundamentals

Cisco Learning and Certifications

Network Security, Operations Management

https://www.coursera.org/specializations/cbrops

87,224

The Cybersecurity Specialization covers the fundamental concepts underlying the construction of secure systems, from the hardware to the software to the human-computer interface, with the use of cryptography to secure interactions. These concepts are illustrated with examples drawn from modern practice, and augmented with hands-on exercises involving relevant tools and techniques. Successful participants will develop a way of thinking that is security-oriented, better understanding how to think about adversaries and how to build systems that defend against them.

173

Beginner

Specialization

3 - 6 Months

Create a Profile and Network on LinkedIn

Coursera Project Network

Communication, Professional Development

712

Beginner

Guided Project

Less Than 2 Hours

Introduction to TCP/IP

Yonsei University

Computer Networking, Computer Security Models, Network Architecture, Network Model, Network Security, Network Analysis, Networking Hardware, System Security, Communication, Security Engineering

2.6K

Beginner

Course

1 - 3 Months

Palo Alto Networks Cybersecurity

Palo Alto Networks

Network Security, Security Engineering, Computer Networking, System Security, Software Security, Network Architecture, Cloud Computing, Computer Security Models, Strategy and Operations, Computer Security Incident Management, Operations Management, Security Software, Cyberattacks, Network Model, Security Strategy, Software As A Service, Cloud Applications, Cloud Infrastructure, Leadership and Management, Networking Hardware, Strategy, Cloud Management, Cloud Standards, Cloud Clients, Software-Defined Networking

422

Beginner

Professional Certificate

3 - 6 Months

Get Started with Figma

Coursera Project Network

User Experience, Web Design

707

Beginner

Guided Project

Less Than 2 Hours

Career Discovery

University System of Georgia

Leadership and Management, Communication, Planning, Writing

1.6K

Beginner

Specialization

3 - 6 Months

Network Defense Essentials (NDE)

EC-Council

Security Engineering, Network Security, System Security, Software Security, Cloud Computing, Security Software, Internet Of Things, Kubernetes, Mobile Security, Network Architecture, Computer Networking

52

Beginner

Course

1 - 3 Months

Introduction to CRM with HubSpot

Coursera Project Network

Customer Relationship Management, Marketing, Data Management, Leadership and Management

668

Beginner

Guided Project

Less Than 2 Hours

Networks and Communications Security

ISC2

Network Security, Communication

254

Beginner

Course

1 - 3 Months

Neural Network from Scratch in TensorFlow

Coursera Project Network

Artificial Neural Networks, Deep Learning, Machine Learning, Data Science, Tensorflow

276

Intermediate

Guided Project

Less Than 2 Hours

IBM Business Intelligence (BI) Analyst

SkillUp EdTech

Data Management, Databases, SQL, Data Visualization, Database Administration, Database Application, Database Design, Microsoft Excel, Data Structures, Data Architecture, Database Theory, Spreadsheet Software, Data Model, Data Warehousing, Python Programming, Data Analysis, Data Analysis Software, NoSQL, PostgreSQL, Professional Development, Plot (Graphics), Business Analysis, Computational Thinking, Statistical Visualization, Data Mining, Data Science, Data Visualization Software, R Programming, Business Intelligence, Forecasting, Interactive Data Visualization, Statistical Analysis

9.8K

Beginner

Professional Certificate

3 - 6 Months

Google Cloud Database Engineer

Google Cloud

Databases, Cloud Computing, Google Cloud Platform, Data Management, Cloud Platforms, Database Administration, Database Application, SQL, Cloud Infrastructure, Cloud Storage, Data Analysis, Google App Engine, Kubernetes, PostgreSQL

https://www.coursera.org/specializations/google-cloud-database-engineer

301,133

This course introduces the Google Cloud big data and machine learning products and services that support the data-to-AI lifecycle. It explores the processes, challenges, and benefits of building a big data pipeline and machine learning models with Vertex AI on Google Cloud.

48K

Intermediate

Specialization

3 - 6 Months

Preparing for Google Cloud Certification: Cloud DevOps Engineer

Google Cloud

DevOps, Communication, Leadership and Management, Collaboration, Design and Product, Entrepreneurship, Product Development, Product Management, Strategy and Operations, Operations Management, Cloud Computing, Cloud Infrastructure, Cloud Platforms, Cloud Storage, Culture, Docker (Software), Google App Engine, Google Cloud Platform, Kubernetes

https://www.coursera.org/professional-certificates/sre-devops-engineer-google-cloud

32,789

This program provides the skills you need to advance your career as a data engineer and provides training to support your preparation for the industry-recognized Google Cloud Professional DevOps EngineerOpens in a new tab certification. 87% of Google Cloud certified users feel more confident in their cloud skills. You'll also have the opportunity to practice key job skills using Google Cloud to build software delivery pipelines, deploy and monitor services, and manage and learn from incidents. You will learn to apply SRE principles to a service, techniques for monitoring, troubleshooting, and improving infrastructure and application performance among other things. Your journey to Google Cloud certification: 1) Complete the Coursera Site Reliability Engineering and DevOps Professional Certificate 2) Review other recommended learning resources for the Google Cloud Professional Cloud DevOps Engineer certification examOpens in a new tab 3) Review the Professional Cloud DevOps Engineer exam guide Opens in a new tab 4) Take the Professional Cloud DevOps Engineer practice examOpens in a new tab 5) RegisterOpens in a new tab for the Google Cloud certification exam (Can be taken remotely or at a test center) Applied Learning Project This professional certificate incorporates hands-on labs using our Qwiklabs platform. These hands on components will let you apply the skills you learn in the video lectures. Projects will incorporate topics such as Google Cloud Platform products, which are used and configured within Qwiklabs. You can expect to gain practical hands-on experience with the concepts explained throughout the modules.

53K

Beginner

Professional Certificate

3 - 6 Months

AI for Medicine

DeepLearning.AI

Machine Learning, Machine Learning Algorithms, Deep Learning, Python Programming, Artificial Neural Networks, Statistical Programming, Probability & Statistics

https://www.coursera.org/specializations/ai-for-medicine

41,525

AI is transforming the practice of medicine. It’s helping doctors diagnose patients more accurately, make predictions about patients’ future health, and recommend better treatments. This three-course Specialization will give you practical experience in applying machine learning to concrete problems in medicine. These courses go beyond the foundations of deep learning to teach you the nuances in applying AI to medical use cases. If you are new to deep learning or want to get a deeper foundation of how neural networks work, we recommend taking the Deep Learning SpecializationOpens in a new tab. Applied Learning Project Medicine is one of the fastest-growing and important application areas, with unique challenges like handling missing data. You’ll start by learning the nuances of working with 2D and 3D medical image data. You’ll then apply tree-based models to improve patient survival estimates. You’ll also use data from randomized trials to recommend treatments more suited to individual patients. Finally, you’ll explore how natural language extraction can more efficiently label medical datasets.

2.3K

Intermediate

Specialization

1 - 3 Months

TensorFlow: Advanced Techniques

DeepLearning.AI

Deep Learning, Machine Learning, Tensorflow, Artificial Neural Networks, Applied Machine Learning, Python Programming, Machine Learning Algorithms, Human Learning, Computer Vision, Computer Programming, Network Model, Machine Learning Software, Network Architecture, Training, Visualization (Computer Graphics), Computer Graphic Techniques, Strategy

https://www.coursera.org/specializations/tensorflow-advanced-techniques

25,821

TensorFlow is an end-to-end open-source platform for machine learning. It has a comprehensive, flexible ecosystem of tools, libraries, and community resources that lets researchers push the state-of-the-art in ML, and developers easily build and deploy ML-powered applications. TensorFlow is commonly used for machine learning applications such as voice recognition and detection, Google Translate, image recognition, and natural language processing. Expand your knowledge of the Functional API and build exotic non-sequential model types. Learn how to optimize training in different environments with multiple processors and chip types and get introduced to advanced computer vision scenarios such as object detection, image segmentation, and interpreting convolutions. Explore generative deep learning including the ways AIs can create new content from Style Transfer to Auto Encoding, VAEs, and GANs. This Specialization is for software and machine learning engineers with a foundational understanding of TensorFlow who are looking to expand their knowledge and skill set by learning advanced TensorFlow features to build powerful models. Looking for a place to start? Master foundational basics with the DeepLearning.AI TensorFlow Developer Professional CertificateOpens in a new tab. Ready to deploy your models to the world? Learn how to go live with the TensorFlow: Data and Deployment SpecializationOpens in a new tab. Applied Learning Project In this Specialization, you will gain practical knowledge of and hands-on training in advanced TensorFlow techniques such as style transfer, object detection, and generative machine learning. Course 1: Understand the underlying basis of the Functional API and build exotic non-sequential model types, custom loss functions, and layers. Course 2: Learn how optimization works and how to use GradientTape and Autograph. Optimize training in different environments with multiple processors and chip types. Course 3: Practice object detection, image segmentation, and visual interpretation of convolutions. Course 4: Explore generative deep learning and how AIs can create new content, from Style Transfer through Auto Encoding and VAEs to Generative Adversarial Networks.

1.4K

Intermediate

Specialization

3 - 6 Months

Google Cloud Fundamentals: Core Infrastructure

Google Cloud

Cloud Computing, Cloud Infrastructure, Cloud Platforms, Cloud Storage, Google App Engine, Google Cloud Platform, Kubernetes

https://www.coursera.org/learn/gcp-fundamentals

40,408

The Cloud Digital Leader training consists of a course series designed to give you foundational knowledge about cloud technology and data. This training also offers an overview of Google Cloud products and services that enable organizations’ digital transformation. This training will empower you and your team(s) to contribute to cloud-related business initiatives across your organization. This training builds knowledge in these areas: General cloud knowledge General Google Cloud knowledge Google Cloud products and services Digital transformation, data, and AI/ML Modernizing company IT infrastructure and applications Applied Learning Project Students will have an opportunity to validate their knowledge gained throughout each of the courses with practice and graded assessments at the end of each module and for each course. Practice and graded assessments are used to validate and demonstrate learning outcomes.

48K

Beginner

Course

1 - 3 Months

Introduction to Cloud Computing

IBM

Cloud Computing, Cloud Applications, Cloud Infrastructure, Cloud Platforms, Cloud Storage, DevOps, IBM Cloud

https://www.coursera.org/learn/introduction-to-cloud

15,934

This course introduces you to a framework for successful and ethical medical data mining. We will explore the variety of clinical data collected during the delivery of healthcare. You will learn to construct analysis-ready datasets and apply computational procedures to answer clinical questions. We will also explore issues of fairness and bias that may arise when we leverage healthcare data to make decisions about patient care. In support of improving patient care, Stanford Medicine is jointly accredited by the Accreditation Council for Continuing Medical Education (ACCME), the Accreditation Council for Pharmacy Education (ACPE), and the American Nurses Credentialing Center (ANCC), to provide continuing education for the healthcare team. Visit the FAQs below for important information regarding 1) Date of the original release and expiration date; 2) Accreditation and Credit Designation statements; 3) Disclosure of financial relationships for every person in control of activity content.

5K

Beginner

Course

1 - 3 Months

Configuration Management and the Cloud

Google

Cloud Computing, Cloud Platforms, Google Cloud Platform, Leadership and Management

2.4K

Beginner

Course

1 - 4 Weeks

Introduction to Microsoft Azure Cloud Services

Microsoft

Cloud Applications, Cloud Computing, Cloud Infrastructure, Microsoft Azure, Cloud Management, Cloud Platforms, Cloud Standards, Cloud-Based Integration, Software As A Service, Cloud Storage, Databases

https://www.coursera.org/learn/microsoft-azure-cloud-services

461,103

Learn how to think the way mathematicians do – a powerful cognitive process developed over thousands of years. Mathematical thinking is not the same as doing mathematics – at least not as mathematics is typically presented in our school system. School math typically focuses on learning procedures to solve highly stereotyped problems. Professional mathematicians think a certain way to solve real problems, problems that can arise from the everyday world, or from science, or from within mathematics itself. The key to success in school math is to learn to think inside-the-box. In contrast, a key feature of mathematical thinking is thinking outside-the-box – a valuable ability in today’s world. This course helps to develop that crucial way of thinking.

1.9K

Beginner

Course

1 - 4 Weeks

AWS Cloud Practitioner Essentials

Amazon Web Services

Amazon Web Services, Cloud Computing

https://www.coursera.org/learn/aws-cloud-practitioner-essentials

111,494

Welcome to AWS Cloud Practitioner Essentials. If you’re new to the cloud, whether you’re in a technical or non-technical role such as finance, legal, sales, marketing, this course will provide you with an understanding of fundamental AWS Cloud concepts to help you gain confidence to contribute to your organization’s cloud initiatives. This course is also the starting point to prepare for your AWS Certified Cloud Practitioner certification whenever it’s convenient for you. After you complete the course, you’ll understand the benefits of the AWS Cloud and the basics of its global infrastructure. You’ll be able to describe and provide an example of the core AWS services, including compute, network, databases, and storage. For the finance-minded, you’ll be able to articulate the financial benefits of the AWS Cloud, define core billing and pricing models, and learn how to use pricing tools to make cost-effective choices for AWS services.

1.5K

Beginner

Course

1 - 3 Months

Cloud Computing Basics (Cloud 101)

LearnQuest

Cloud Computing, Cloud Platforms, Software As A Service, Cloud Storage, Google Cloud Platform, Internet Of Things, Microsoft Azure

6.4K

Beginner

Course

1 - 3 Months

Digital Transformation Using AI/ML with Google Cloud

Google Cloud

Cloud Computing, Google Cloud Platform, Business Transformation, Business Analysis, Data Management, Cloud Applications, Cloud Clients, Cloud Infrastructure, Cloud Platforms, Cloud-Based Integration, Data Analysis, Kubernetes, Machine Learning, Other Cloud Platforms and Tools, Applied Machine Learning, Human Learning, Innovation, Machine Learning Software, Strategy, Strategy and Operations, Customer Analysis, Machine Learning Algorithms, Cloud API, Google App Engine, Business Intelligence, Organizational Development, Algorithms, Leadership and Management, Data Architecture

https://www.coursera.org/specializations/digital-transformation-using-ai-ml-with-google-cloud

179,980

Not so long ago, the job of product manager was about assessing market data, creating requirements, and managing the hand-off to sales/marketing. Maybe you’d talk to a customer somewhere in there and they’d tell you what features they wanted. But companies that manage product that way are dying. Being a product person today is a new game, and product managers are at the center of it. Today, particularly if your product is mostly digital, you might update it several times a day. Massive troves of data are available for making decisions and, at the same time, deep insights into customer motivation and experience are more important than ever. The job of the modern product manager is to charter a direction and create a successful working environment for all the actors involved in product success. It’s not a simple job or an easy job, but it is a meaningful job where you’ll be learning all the time. This course will help you along your learning journey and prepare you with the skills and perspective you need to: Create the actionable focus to successfully manage your product (week 1) Focus your work using modern product management methods (week 2) Manage new products and explore new product ideas (week 3) Manage and amplify existing products (week 4) This course is ideal for current product or general managers interested in today's modern product management methods. Please note that there are new additions to this course and subtitles for these videos will soon be available. This course was developed with the generous support of the Batten Institute at UVA’s Darden School of Business. The Batten Institute’s mission is to improve the world through entrepreneurship and innovation: www.batteninstitute.org.

6.8K

Beginner

Specialization

3 - 6 Months

Cloud-Native Development with OpenShift and Kubernetes

Red Hat

Cloud Applications, Kubernetes, Cloud Computing, Cloud Platforms

https://www.coursera.org/specializations/cloud-native-development-openshift-kubernetes

7,750

This specialization is designed for individuals and teams that will be running or interacting with clinical trials. In four courses, learners will develop insights and build the skills they need to design, manage, and monitor clinical trials as well as analyze, document, and communicate the results. Learners will also learn best practices regarding ethics, safety, participant recruitment, regulatory compliance, and reporting standards. The core principles and skills of the specialization will lay the foundation for a successful career in the field. Applied Learning Project Learners will demonstrate their mastery of skills, including trial design, data collection and management, statistical monitoring, trial ethics, participant recruitment and retention, data analysis, communication of results, and advanced operational techniques.

114

Intermediate

Specialization

3 - 6 Months

Essential Google Cloud Infrastructure: Foundation

Google Cloud

Cloud Applications, Cloud Computing, Cloud Infrastructure, Cloud Management, Cloud Platforms, Cloud-Based Integration, Computer Networking, Computer Programming, Google Cloud Platform, Network Architecture

17K

Intermediate

Course

1 - 4 Weeks

Moving to the Cloud

The University of Melbourne

Cloud Computing, Leadership and Management, Strategy and Operations, Change Management, Cloud Clients, Strategy, Cloud Infrastructure, Cloud Management, Cloud Standards

227

Beginner

Course

1 - 3 Months

Google Cloud Digital Leader Training

Google Cloud

Cloud Computing, Cloud Infrastructure, Google Cloud Platform, Cloud Management, Cloud Platforms, Cloud Applications, Cloud-Based Integration, Cloud Clients, Kubernetes, Other Cloud Platforms and Tools, Cloud API, Data Management, DevOps, System Security, Data Architecture, Google App Engine, Collaboration, Innovation, Leadership and Management, Operations Management, Security Engineering, Machine Learning

https://www.coursera.org/professional-certificates/google-cloud-digital-leader-training

2,902

A Database Engineer designs, creates, manages, migrates, and troubleshoots databases used by applications to store and retrieve data. This learning path guides you through a curated collection of on-demand courses, labs, and skill badges that provide you with real-world, hands-on experience using Google Cloud technologies essential to the Database Engineer role. Once you complete the path, check out our catalog for 700+ labs and courses to keep going on your professional journey. Applied Learning Project This specialization incorporates labs using our Qwiklabs platform. These components will let you gain practical hands-on experience with the concepts explained in the video modules. In addition, you will learn about and practice working with Google Cloud databases such as Cloud SQL, Cloud Spanner, and Bigtable.

3.8K

Beginner

Professional Certificate

3 - 6 Months

Internet of Things and AI Cloud

University of California San Diego

Computer Networking, Internet Of Things, Communication, Computer Vision, Software-Defined Networking, Computer Programming, Cloud Computing, Python Programming

1.7K

Intermediate

Specialization

3 - 6 Months

Create a Virtual Private Cloud (VPC) Using AWS

Coursera Project Network

Cloud Computing

126

Beginner

Guided Project

Less Than 2 Hours

Building Scalable Java Microservices with Spring Boot and Spring Cloud

Google Cloud

Cloud Applications, Cloud Computing, Cloud Infrastructure, Cloud Platforms, Google App Engine, Google Cloud Platform, Java Programming, Kubernetes

1.2K

Intermediate

Course

1 - 4 Weeks

Preparing for your Professional Cloud Architect Journey

Google Cloud

Google Cloud Platform, Cloud Computing, Cloud Engineering, Critical Thinking, Cloud Applications, Cloud Platforms, Computer Security Models, Devops Tools, Operational Analysis, Software Testing

1.3K

Advanced

Course

1 - 3 Months

Getting started with Google Workspace

Google Cloud

Collaboration, Communication, Google Cloud Platform, Cloud Applications, User Experience, Cloud Platforms, Leadership and Management, Cloud Computing, Business Communication, Organizational Development, Google App Engine, Cloud Storage, Data Management, Planning, Problem Solving, Business Analysis, Spreadsheet Software, Business Process Management, Data Visualization, Other Cloud Platforms and Tools, Project Management, Writing, Professional Development, Data Analysis, Strategy, Exploratory Data Analysis, Design and Product, Visual Design, Graphic Design

https://www.coursera.org/specializations/getting-started-with-google-workspace

98,539

This course is for users who want to learn how to write SAS programs to access, explore, prepare, and analyze data. It is the entry point to learning SAS programming for data science, machine learning, and artificial intelligence. It is a prerequisite to many other SAS courses. By the end of this course, you will know how to use SAS Studio to write and submit SAS programs that access SAS, Microsoft Excel, and text data. You will know how to explore and validate data, prepare data by subsetting rows and computing new columns, analyze and report on data, export data and results to other formats, use SQL in SAS to query and join tables. Prerequisites: Learners should have experience using computer software. Specifically, you should be able to understand file structures and system commands on your operating systems and access data files on your operating systems. No prior SAS experience is needed.

1.4K

Beginner

Specialization

3 - 6 Months

Starting Your Career with AWS Cloud

Amazon Web Services

Cloud Computing

47

Beginner

Specialization

1 - 3 Months

Managing Cloud-native Applications with Kubernetes

Red Hat

Cloud Applications, Kubernetes, Cloud Computing, Cloud Platforms

35

Intermediate

Course

1 - 4 Weeks

Fundamentals of Cloud Computing

LearnQuest

Security Engineering, Network Security, Cloud Computing

21

Mixed

Course

1 - 4 Weeks

Exam Prep: AWS Certified Cloud Practitioner Foundations

Amazon Web Services

Cloud Computing

56

Beginner

Course

1 - 4 Weeks

Introduction to SQL for BigQuery and Cloud SQL

Google Cloud

Cloud Computing, SQL

70

Beginner

Project

Less Than 2 Hours

Google Cloud Product Fundamentals en Español

Google Cloud

Google Cloud Platform, Cloud Computing, Planning

59

Beginner

Course

1 - 3 Months

App Deployment, Debugging, and Performance

Google Cloud

Cloud Computing, Cloud Platforms, Google Cloud Platform

1.2K

Intermediate

Course

1 - 3 Months

Understanding Google Cloud Security and Operations

Google Cloud

Cloud Computing, Cloud Infrastructure, Cloud Management, Google Cloud Platform, Cloud Applications, Collaboration, Leadership and Management, Operations Management, Security Engineering, System Security, DevOps

595

Beginner

Course

1 - 3 Months

Foundations of Red Hat Cloud-native Development

Red Hat

Cloud Applications, Cloud Computing, Kubernetes, Cloud Platforms

86

Intermediate

Course

1 - 4 Weeks

Essential Cloud Infrastructure: Core Services 日本語版

Google Cloud

Cloud Computing, Google Cloud Platform

165

Intermediate

Course

1 - 3 Months

Elastic Cloud Infrastructure: Scaling and Automation em Português Brasileiro

Google Cloud

Cloud Computing, Google Cloud Platform

122

Intermediate

Course

1 - 3 Months

Innovating with Data and Google Cloud

Google Cloud

Cloud Computing, Data Management, Machine Learning, Cloud Platforms, Google Cloud Platform

735

Beginner

Course

1 - 3 Months

Mitigating Security Vulnerabilities on Google Cloud

Google Cloud

Cloud Computing, Cloud Platforms, Computer Security Models, Google Cloud Platform, Network Security, Security Engineering, Security Software, Security Strategy, Software Security, System Security

709

Intermediate

Course

1 - 4 Weeks

Google Cloud Big Data and Machine Learning Fundamentals

Google Cloud

Big Data, Cloud Computing, Cloud Platforms, Google Cloud Platform, Human Learning, Machine Learning

https://www.coursera.org/learn/gcp-big-data-ml-fundamentals

37,959

Get professional training designed by Google and take the next step in your career with advanced skills in the high-growth field of business intelligence. There are over 166,000 open jobs in business intelligence and the median salary for entry-level roles is $96,000.¹ Business intelligence professionals collect, organize, interpret, and report on data to help organizations make informed business decisions. Some responsibilities include measuring performance, tracking revenue or spending, and monitoring progress. This certificate builds on your data analytics skills and experience to take your career to the next level. It's designed for graduates of the Google Data Analytics CertificateOpens in a new tab or people with equivalent data analytics experience. Expand your knowledge with practical, hands-on projects, featuring BigQuery, SQL, and Tableau. After three courses, you’ll be prepared for jobs like business intelligence analyst, business intelligence engineer, business intelligence developer, and more. At under 10 hours a week, the certificate program can be completed in less than two months. Upon completion, you can apply for jobs with Google and over 150 U.S. employers, including Deloitte, Target, and Verizon. 75% of certificate graduates report a positive career outcome (e.g., new job, promotion or raise) within six months of completion2 ¹Lightcast™ US Job Postings (Last 12 Months: 1/1/2022 – 12/31/2022)  2Based on program graduate survey responses, US 2022 Applied Learning Project This program includes over 70 hours of instruction and 50+ practice-based assessments, which will help you simulate real-world business intelligence scenarios that are critical for success in the workplace. The content is highly interactive and exclusively developed by Google employees with decades of experience in business intelligence. Through a mix of videos, assessments, and hands-on labs, you’ll get introduced to BI tools and platforms and key technical skills required for an entry-level job. Platforms and tools you will learn include: BigQuery, SQL, Tableau In addition to expert training and hands-on projects, you'll complete a portfolio project that you can share with potential employers to showcase your new skill set. Learn concrete skills that top employers are hiring for right now.

16K

Beginner

Course

1 - 3 Months

Introduction to Containers w/ Docker, Kubernetes & OpenShift

IBM

Kubernetes, Docker (Software), Cloud Computing

676

Intermediate

Course

1 - 3 Months

Reliable Cloud Infrastructure: Design and Process 日本語版

Google Cloud

Cloud Computing, Google Cloud Platform, Cloud Platforms, Computer Architecture, Cloud Infrastructure, Computer Networking, Cloud Management, Docker (Software), Network Architecture

80

Intermediate

Course

1 - 3 Months

Getting Started with Terraform for Google Cloud

Google Cloud

Cloud Infrastructure, DevOps, Cloud Computing, Cloud Management, Cloud Platforms, Google Cloud Platform

30

Beginner

Course

1 - 3 Months

API Security on Google Cloud's Apigee API Platform

Google Cloud

Cloud Computing

812

Beginner

Course

1 - 4 Weeks