<commit_before>---
layout: page
title: MOOC
permalink: /mooc/
image: /assets/images/books_background.jpg
---

# MOOC - Online Course List

#### Currently Learning:

- Statistical Inference 2nd edition by <NAME> - Page 66 of 686

Chapter 1 - Exercise Problem 1.18
Chapter 2 - Exercise 2.11 - Continue
Chapter 3 - Exercise - Start
Chapter 4 - Exercise 4.5
Chapter 5 - Exercise - Start
Chapter 7 - MLE - Example 7.2.5


- Applied Regression Analysis, 3rd Edition by <NAME>, <NAME> - Page 104 of 704
Exercises Chapter 1 - 3 - Start
Chapter 4 - Start

- Categorical Data Analysis 3rd Edition by <NAME> - Page 34 of 742 - Mid P-value & Small Sample Inference
Chapter 2 - Section 2.4.3 - Summary Measures of Association | Problem Set - 2.24, 2.25

- Sams Teach Yourself SQL in 24 Hours - Page 136 of 495 - Chapter 8

- Time Series Analysis and Its Applications by <NAME> • <NAME> - Page 1 of 202


- The Deep Learning Textbook by <NAME>, <NAME> and <NAME> - MIT Press book - 185/802 - Chapter 6 - 6.1 - Learning XOR

- CS 20: Tensorflow for Deep Learning Research by Stanford by <NAME> - Week 2 - Operations

- How to Win a Data Science Competition: Learn from Top Kagglers by National Research University Higher School of Economics on Coursera - Week 1 - Feature Preprocessing - Handling Missing Values

- Cracking the Coding Interview by <NAME>, 5th Edition - Page 82 of 510 - Interview Questions - 1.1

- The Algorithm Design Manual by <NAME> - Page 84 of 739 - Dictionaries

- Data Structures and Algorithms in Python by <NAME>, <NAME>, and <NAME> - Page 183 of 770 | Chapter 3 - Remaining

- Practical Statistics for Data Scientists by <NAME>, <NAME> - Page 97 of 317 - Chapter 3

- [Internals of CPython - Version 1](https://intopython.com/) by <NAME> - Page 0 of 100
-----------------------------------------------------------------------------------------------------------------------------

- Python for Data Analysis by <NAME>, published by O'Reilly Media - Page 95 of 470 - Chapter 4 - NumPy




- [Coding the Matrix](https://cs.brown.edu/video/channels/coding-matrix-fall-2014/)
- [Numerical Linear Algebra](https://github.com/fastai/numerical-linear-algebra)






- [Valuation](https://www.youtube.com/playlist?list=PLUkh9m2BorqkNzSSPrCDkO2jlufVCinVw) by <NAME>
- [Valuation Tools Webcasts](https://www.youtube.com/playlist?list=PLUkh9m2BorqmRAGzJb5OIvTAKZZu9HWF-) by <NAME>
------------------------------------------------------------------------------------------------------------------------------

## 2018

###### MOOCS:
1. SQL Basics by Vertablo Academy
2. Operating on Data in SQL by Vertablo Academy
3. Creating Tables in SQL by Vertablo Academy
4. Neural Networks and Deep Learning by deeplearning.ai on Coursera
5. [Introduction to Linux LFS101x](https://www.edx.org/course/introduction-linux-linuxfoundationx-lfs101x-1) by Linux Foundation on edX


###### Books:
1. Introduction to Statistical Learning by <NAME>, <NAME>, <NAME> and <NAME>
2. From Python to Numpy by <NAME> - http://www.labri.fr/perso/nrougier/from-python-to-numpy/

###### List of Interesting Papers:
1. Bagging Equalizes Influence - <NAME> (2004) 55: 251. - https://doi.org/10.1023/B:MACH.0000027783.34431.42
2. A Few Useful Things to Know about Machine Learning - <NAME> - https://homes.cs.washington.edu/~pedrod/papers/cacm12.pdf
3. Random Forests - <NAME>, Statistics Department University of California - https://www.stat.berkeley.edu/~breiman/randomforest2001.pdf

## 2017

###### MOOC:
- [STAT 100: Statistical Concepts and Reasoning](https://onlinecourses.science.psu.edu/statprogram/stat100) by Penn State
- [STAT 200: Elementary Statistics](https://onlinecourses.science.psu.edu/statprogram/stat200) by Penn State
- [STAT 414: Intro Probability Theory](https://onlinecourses.science.psu.edu/stat414/) by Penn State
- [STAT 415: Intro Mathematical Statistics](https://onlinecourses.science.psu.edu/stat414/node/213) by Penn State
- [The Data Scientist’s Toolbox](https://www.coursera.org/learn/data-scientists-tools) by Johns Hopkins University
- [R Programming](https://www.coursera.org/learn/r-programming) by Johns Hopkins University
- [Swirl R Programming](http://swirlstats.com/)
- [Startup School - How to Start a Startup - CS183F](https://www.youtube.com/playlist?list=PLoROMvodv4rNpMrTeeh-627Lajh6uSUgY) by Y Combinator
- [An Intuitive Introduction to Probability](https://www.coursera.org/learn/introductiontoprobability) by University of Zurich on Coursera
- [Analyzing Big Data With Twitter](https://www.youtube.com/playlist?list=PLE8C1256A28C1487F) by UC Berkeley - School of Information
- [Statistics 110: Probability](https://projects.iq.harvard.edu/stat110/home) by Prof. <NAME>, Harvard
- [MIT OCW Single Variable Calculus 18.01](https://www.youtube.com/playlist?list=PL590CCC2BC5AF3BC1)
- [MIT 18.06 Linear Algebra](https://www.youtube.com/playlist?list=PLE7DDD91010BC51F8) by <NAME> 
- [MIT 18.06SC Linear Algebra Recitations](https://www.youtube.com/playlist?list=PL221E2BBF13BECF6C) by <NAME> 
- [Machine Learning: Regression](https://www.coursera.org/learn/ml-regression) by University of Washington
- [Algorithmic Toolbox](https://www.coursera.org/learn/algorithmic-toolbox/) by University of California, San Diego & Higher School of Economics
- [The Zen of Saving](https://app.novoed.com/zen-of-saving-1)

###### Books:
- [R Programming for Data Science](https://leanpub.com/rprogramming)
- Linear Algebra and its Applications by Prof. <NAME>, Fourth Edition
- Support Vector Machine Succinctly by <NAME>
- Schaum's Linear Algebra
- Schaum's Advanced Calculus
- Single and Multivariate Calculus by <NAME> al
- A First Course in Probability by <NAME>
- Statistics and Data Analysis: From Elementary to Intermediate by <NAME> and <NAME>
- Programming Hive




## 2016

###### MOOC:
- [The Data Scientist’s Toolbox](https://www.coursera.org/learn/data-scientists-tools) by Johns Hopkins University on Coursera
- [The Analytics Edge](https://www.edx.org/course/analytics-edge-mitx-15-071x-2) by MITx on edX
- [CS105x Introduction to Apache Spark](https://courses.edx.org/courses/course-v1:BerkeleyX+CS105x+1T2016) by BerkeleyX on edX
- [Introduction to DevOps](https://www.edx.org/course/introduction-devops-microsoft-dev212x) by Microsoft on edX
- [Deep Learning](https://developer.nvidia.com/deep-learning-courses) by NVIDIA
- [Programming Methodology](https://see.stanford.edu/Course/CS106A) by Stanford
- [Model Thinking - University of Michigan](https://www.coursera.org/learn/model-thinking) by Coursera | [Certificate](https://github.com/KartikKannapur/kartikkannapur.github.io/blob/master/mooc_certificates/Model_Thinking_Coursera_Michigan.png)
- [SQL Queries](https://academy.vertabelo.com/course/sql-queries) by Vertabelo
- [Operating on Data in SQL](https://academy.vertabelo.com/course/operating-on-data-in-sql) by Vertabelo
- [Creating Tables in SQL](https://academy.vertabelo.com/course/creating-tables-in-sql) by Vertabelo
- [Intro to SQL: Querying and managing data](https://www.khanacademy.org/computing/computer-programming/sql) by Khan Academy
- [MIT Launch X – Becoming an Entrepreneur](https://www.edx.org/course/becoming-entrepreneur-mitx-launch-x) by edX
- [MongoDB for Python Developers](https://university.mongodb.com/courses/M101P/about) by MongoDB University | [Certificate](https://github.com/KartikKannapur/kartikkannapur.github.io/blob/master/mooc_certificates/MongoDB_M101P_Certificate.pdf)

###### Books:
- Learning R
- Lucene in Action by <NAME> and <NAME>
- [Elasticsearch: The Definitive Guide](https://www.elastic.co/guide/en/elasticsearch/guide/current/index.html)
<commit_msg>AMS 570 - Update<commit_after>---
layout: page
title: MOOC
permalink: /mooc/
image: /assets/images/books_background.jpg
---

# MOOC - Online Course List

#### Currently Learning:

- Statistical Inference 2nd edition by <NAME> - Page 66 of 686

Chapter 1 - Exercise Problem 1.18
Chapter 2 - Exercise 2.16 - Continue
Chapter 3 - Exercise - Start
Chapter 4 - Exercise 4.5
Chapter 5 - Exercise - Start
Chapter 7 - MLE - Example 7.2.5


- Applied Regression Analysis, 3rd Edition by <NAME>, <NAME> - Page 104 of 704
Exercises Chapter 1 - 3 - Start
Chapter 4 - Start

- Categorical Data Analysis 3rd Edition by <NAME> - Page 34 of 742 - Mid P-value & Small Sample Inference
Chapter 2 - Section 2.4.3 - Summary Measures of Association | Problem Set - 2.24, 2.25

- Sams Teach Yourself SQL in 24 Hours - Page 136 of 495 - Chapter 8

- Time Series Analysis and Its Applications by <NAME> • <NAME> - Page 1 of 202


- The Deep Learning Textbook by <NAME>, <NAME> and <NAME> - MIT Press book - 185/802 - Chapter 6 - 6.1 - Learning XOR

- CS 20: Tensorflow for Deep Learning Research by Stanford by <NAME> - Week 2 - Operations

- How to Win a Data Science Competition: Learn from Top Kagglers by National Research University Higher School of Economics on Coursera - Week 1 - Feature Preprocessing - Handling Missing Values

- Cracking the Coding Interview by <NAME>, 5th Edition - Page 82 of 510 - Interview Questions - 1.1

- The Algorithm Design Manual by <NAME> - Page 84 of 739 - Dictionaries

- Data Structures and Algorithms in Python by <NAME>, <NAME>, and <NAME> - Page 183 of 770 | Chapter 3 - Remaining

- Practical Statistics for Data Scientists by <NAME>, <NAME> - Page 97 of 317 - Chapter 3

- [Internals of CPython - Version 1](https://intopython.com/) by <NAME> - Page 0 of 100
-----------------------------------------------------------------------------------------------------------------------------

- Python for Data Analysis by <NAME>, published by O'Reilly Media - Page 95 of 470 - Chapter 4 - NumPy




- [Coding the Matrix](https://cs.brown.edu/video/channels/coding-matrix-fall-2014/)
- [Numerical Linear Algebra](https://github.com/fastai/numerical-linear-algebra)






- [Valuation](https://www.youtube.com/playlist?list=PLUkh9m2BorqkNzSSPrCDkO2jlufVCinVw) by <NAME>odaran
- [Valuation Tools Webcasts](https://www.youtube.com/playlist?list=PLUkh9m2BorqmRAGzJb5OIvTAKZZu9HWF-) by <NAME>
------------------------------------------------------------------------------------------------------------------------------

## 2018

###### MOOCS:
1. SQL Basics by Vertablo Academy
2. Operating on Data in SQL by Vertablo Academy
3. Creating Tables in SQL by Vertablo Academy
4. Neural Networks and Deep Learning by deeplearning.ai on Coursera
5. [Introduction to Linux LFS101x](https://www.edx.org/course/introduction-linux-linuxfoundationx-lfs101x-1) by Linux Foundation on edX


###### Books:
1. Introduction to Statistical Learning by <NAME>, <NAME>, <NAME> and <NAME>
2. From Python to Numpy by <NAME> - http://www.labri.fr/perso/nrougier/from-python-to-numpy/

###### List of Interesting Papers:
1. Bagging Equalizes Influence - Grandvalet, Y. Mach Learn (2004) 55: 251. - https://doi.org/10.1023/B:MACH.0000027783.34431.42
2. A Few Useful Things to Know about Machine Learning - <NAME> - https://homes.cs.washington.edu/~pedrod/papers/cacm12.pdf
3. Random Forests - <NAME>, Statistics Department University of California - https://www.stat.berkeley.edu/~breiman/randomforest2001.pdf

## 2017

###### MOOC:
- [STAT 100: Statistical Concepts and Reasoning](https://onlinecourses.science.psu.edu/statprogram/stat100) by Penn State
- [STAT 200: Elementary Statistics](https://onlinecourses.science.psu.edu/statprogram/stat200) by Penn State
- [STAT 414: Intro Probability Theory](https://onlinecourses.science.psu.edu/stat414/) by Penn State
- [STAT 415: Intro Mathematical Statistics](https://onlinecourses.science.psu.edu/stat414/node/213) by Penn State
- [The Data Scientist’s Toolbox](https://www.coursera.org/learn/data-scientists-tools) by Johns Hopkins University
- [R Programming](https://www.coursera.org/learn/r-programming) by Johns Hopkins University
- [Swirl R Programming](http://swirlstats.com/)
- [Startup School - How to Start a Startup - CS183F](https://www.youtube.com/playlist?list=PLoROMvodv4rNpMrTeeh-627Lajh6uSUgY) by Y Combinator
- [An Intuitive Introduction to Probability](https://www.coursera.org/learn/introductiontoprobability) by University of Zurich on Coursera
- [Analyzing Big Data With Twitter](https://www.youtube.com/playlist?list=PLE8C1256A28C1487F) by UC Berkeley - School of Information
- [Statistics 110: Probability](https://projects.iq.harvard.edu/stat110/home) by Prof. <NAME>, Harvard
- [MIT OCW Single Variable Calculus 18.01](https://www.youtube.com/playlist?list=PL590CCC2BC5AF3BC1)
- [MIT 18.06 Linear Algebra](https://www.youtube.com/playlist?list=PLE7DDD91010BC51F8) by <NAME> 
- [MIT 18.06SC Linear Algebra Recitations](https://www.youtube.com/playlist?list=PL221E2BBF13BECF6C) by <NAME> 
- [Machine Learning: Regression](https://www.coursera.org/learn/ml-regression) by University of Washington
- [Algorithmic Toolbox](https://www.coursera.org/learn/algorithmic-toolbox/) by University of California, San Diego & Higher School of Economics
- [The Zen of Saving](https://app.novoed.com/zen-of-saving-1)

###### Books:
- [R Programming for Data Science](https://leanpub.com/rprogramming)
- Linear Algebra and its Applications by Prof. <NAME>, Fourth Edition
- Support Vector Machine Succinctly by <NAME>
- Schaum's Linear Algebra
- Schaum's Advanced Calculus
- Single and Multivariate Calculus by <NAME> et al
- A First Course in Probability by <NAME>
- Statistics and Data Analysis: From Elementary to Intermediate by <NAME> and <NAME>
- Programming Hive




## 2016

###### MOOC:
- [The Data Scientist’s Toolbox](https://www.coursera.org/learn/data-scientists-tools) by Johns Hopkins University on Coursera
- [The Analytics Edge](https://www.edx.org/course/analytics-edge-mitx-15-071x-2) by MITx on edX
- [CS105x Introduction to Apache Spark](https://courses.edx.org/courses/course-v1:BerkeleyX+CS105x+1T2016) by BerkeleyX on edX
- [Introduction to DevOps](https://www.edx.org/course/introduction-devops-microsoft-dev212x) by Microsoft on edX
- [Deep Learning](https://developer.nvidia.com/deep-learning-courses) by NVIDIA
- [Programming Methodology](https://see.stanford.edu/Course/CS106A) by Stanford
- [Model Thinking - University of Michigan](https://www.coursera.org/learn/model-thinking) by Coursera | [Certificate](https://github.com/KartikKannapur/kartikkannapur.github.io/blob/master/mooc_certificates/Model_Thinking_Coursera_Michigan.png)
- [SQL Queries](https://academy.vertabelo.com/course/sql-queries) by Vertabelo
- [Operating on Data in SQL](https://academy.vertabelo.com/course/operating-on-data-in-sql) by Vertabelo
- [Creating Tables in SQL](https://academy.vertabelo.com/course/creating-tables-in-sql) by Vertabelo
- [Intro to SQL: Querying and managing data](https://www.khanacademy.org/computing/computer-programming/sql) by Khan Academy
- [MIT Launch X – Becoming an Entrepreneur](https://www.edx.org/course/becoming-entrepreneur-mitx-launch-x) by edX
- [MongoDB for Python Developers](https://university.mongodb.com/courses/M101P/about) by MongoDB University | [Certificate](https://github.com/KartikKannapur/kartikkannapur.github.io/blob/master/mooc_certificates/MongoDB_M101P_Certificate.pdf)

###### Books:
- Learning R
- Lucene in Action by <NAME> and <NAME>
- [Elasticsearch: The Definitive Guide](https://www.elastic.co/guide/en/elasticsearch/guide/current/index.html)

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