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.
  • Module Outline:

    Day 1:

  • 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
  • Day 2:

  • 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
  • Day 3:

  • 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
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