Intro to Python for Computer Science and Data Science: Learning to Program with AI, Big Data and The...

Table of Content

“PART 1 CS: Python Fundamentals Quickstart CS 1. Introduction to Computers and Python DS Intro: AI-at the Intersection of CS and DS CS 2. Introduction to Python Programming DS Intro: Basic Descriptive Stats CS 3. Control Statements and Program Development DS Intro: Measures of Central Tendency—Mean, Median, Mode CS 4. Functions DS Intro: Basic Statistics— Measures of Dispersion CS 5. Lists and Tuples DS Intro: Simulation and Static Visualization PART 2 CS: Python Data Structures, Strings and Files CS 6. Dictionaries and Sets DS Intro: Simulation and Dynamic Visualization CS 7. Array-Oriented Programming with NumPy, High-Performance NumPy Arrays DS Intro: Pandas Series and DataFrames CS 8. Strings: A Deeper Look Includes Regular Expressions DS Intro: Pandas, Regular Expressions and Data Wrangling CS 9. Files and Exceptions DS Intro: Loading Datasets from CSV Files into Pandas DataFrames PART 3 CS: Python High-End Topics CS 10. Object-Oriented Programming DS Intro: Time Series and Simple Linear Regression CS 11. Computer Science Thinking: Recursion, Searching, Sorting and Big O CS and DS Other Topics Blog PART 4 AI, Big Data and Cloud Case Studies DS 12. Natural Language Processing (NLP), Web Scraping in the Exercises DS 13. Data Mining Twitter®: Sentiment Analysis, JSON and Web Services DS 14. IBM Watson® and Cognitive Computing DS 15. Machine Learning: Classification, Regression and Clustering DS 16. Deep Learning Convolutional and Recurrent Neural Networks; Reinforcement Learning in the Exercises DS 17. Big Data: Hadoop®, Spark™, NoSQL and IoT”