Python for Data Science: Essentials
The Course Name: Python for Data Science: Essentials
The Duration: 3 Days
Module Description
- This Module is consist of Python for Data Science Essential Topics. Attendees will have essential information on Data Science and Analysis.
- This is pre-requsite of almost all Python Data Science and Machine Learning Courses. Attendees working on Data Analysis, Machine Learning and Artificial Intelligence will find this essential content very useful.
- Python Background
- Quick Review of Python Essentials
- Functional Programming Functions
- - List Comprehensions
- - Lambda Functions
- - map, filter, reduce
- Iterator
- Generator
- Decorator
- LAB: Fibonacci Series with Generator
- Math Background
- Probability Essentials
- Monty Hall and other Problems
- Statistics Basics
- Normal Distribution
- - Mean, Variance, Standard Deviation
- Bayes Theorem
- LAB: High Precision Floating Point Calculation and Probability
- Python for Data Science Labs:
- Harvard Movie Database Project
- Read SQLite3 Movie Database and Analyze Tables
- Understand structures of all tables:
- - movies, stars, directors, ratings, people
- Regular Expressions
- Regex Module
- Search vs. Match
- Find and Replace
- Option Flags
- Special Char Classes
- Database Access
- SQL vs. NoSQL Databases
- SQLite3 Module
- SQL Basics
- CRUD Operations on SQLite3 Database
- Data Analysis Basics
- Scipy Ecosystem
- - numpy
- - pandas
- - matplotlib
- LAB: Symbolic Math with sympy module
- Harvard Movie Database Project
- Review SQL statements and answer the following questions:
- - List all the movies of year 2010 with alphabetical order
- - List all movies having IMDB rating greater than 9.0
- - List all Matrix movies with chronological order
- - List all "Al Pacino" movies between year 2000-2010
- - List top 10 rated "Scarlett Johansson" movies
Module Outline:
Day 1:
Day 2:
Day 3: