Topic 19 – Introduction to Computation and Programming using Python

Why do I need to learn about computation and programming using Python?

Computational thinking and Python are fundamental tools for understanding many modern theories and techniques such as artificial intelligence, machine learning, deep learning, data mining, security, digital imagine processing and natural language processing.

What can I do after finishing learning about computation and programming using Python ?

You will be prepared to learn modern theories and techniques to create  modern  security, machine learning, data mining, image processing or natural language processing software.

That sounds useful! What should I do now?

Please read this "John V. Guttag (2013). Introduction to Computation and Programming using Python. 2nd Edition. The MIT Press" book.

Alternatively, please watch
- this "6.0001 Introduction to Computer Science and Programming in Python. Fall 2016" course (Lecture Notes) and

- this "MIT 6.0002 Introduction to Computational Thinking and Data Science, Fall 2016" course (Lecture Notes)
After finishing reading the book please click Topic 20 - Introduction to Applied Machine Learning to continue.

Topic 18 – Probability & Statistics

Why do I need to learn about probability and statistics?

Probability and statistics are fundamental tools for understanding many modern theories and techniques such as artificial intelligence, machine learning, deep learning, data mining, security, digital imagine processing and natural language processing.

What can I do after finishing learning about probability and statistics?

You will be prepared to learn modern theories and techniques to create modern security, machine learning, data mining, image processing or natural language processing software.

That sounds useful! What should I do now?

Please read this "Dimitri P. Bertsekas and John N. Tsitsiklis (2008). Introduction to Probability" book. Alternatively, please watch this "MIT 6.041SC Probabilistic Systems Analysis and Applied Probability, Fall 2013" course (Lecture Notes).
After finishing reading the book please click Topic 19 - Introduction to Computation and Programming Using Python to continue.

Topic 17 – Linear Algebra

Why do I need to learn about linear algebra?

Linear algebra is a fundamental tool for understanding many modern theories and techniques such as artificial intelligence, machine learning, deep learning, data mining, security, digital imagine processing and natural language processing.

What can I do after finishing learning about linear algebra?

You will be prepared to learn modern theories and techniques to create modern security, machine learning, data mining, image processing or natural language processing software.

That sounds useful! What should I do now?

Please read this "David C. Lay et al. (2016). Linear Algebra and Its Applications. 5th Edition." book.
Alternatively, please watch this "MIT 18.06 Linear Algebra, Spring 2005" course (Lecture Notes).
After finishing the books please click Topic 18 - Probability & Statistics to continue.