Best Fast Track Python Training


course_main_image Fast Track Python

trainerTrainer

Rupesh Saini

Category

Development

Minimum Qualification

BE or equivalent

Duration

2 Months


Course Description

Duration : 16 sessions of 1.5 hours each over 2 months

After completing this program, the student will be able to code complete modules as well as applications. We will be developing some of these applications in class as well as part of the assignments.

During the course we learn all the concepts starting with writing basic programs to calculate to using complex libraries such as Numpy, Beautiful Soup, Pandas and more. We will also learn some of the feature of the language that make it a versatile platform. Along the way, we learn important programming concepts such as modeling, inheritance, functional programming, code optimization techniques , modular testing and much more. We will also learn how to deploy programs and application on cloud servers and touch upon configuring web-servers for python.

After completing this program, the student will be able to code complete modules as well as applications. We will be developing these applications in class as well as part of the assignments.


Session 1 (1.5 hours)

  • 1.1 Setting up the environment
  • 1.2 Setup the Editor
  • 1.3 Hello Date Introduction
  • 1.4 OOPs concepts

Assignment 1

Session 2 (1.5 hours)

  • 2.1 Assignment 1 review
  • 2.2 Variable operators
  • 2.3 Types/Variables
  • 2.4 List/Dict/Tuple
  • 2.5 Collection Operators

Assignment 2

Session 3 (1.5 hours)

  • 3.1 Assignment 2 review
  • 3.2 For Loops
  • 3.3 While Loops
  • 3.4 Ranges
  • 3.5 if..elif.else Statements

Assignment 3

Session 4 (1.5 hours)

  • 4.1 Assignment 3 review
  • 4.2 Python Module - Write a complete script
  • 4.3 Functions
  • 4.4 Functions - Types of Paramaters
  • 4.5 Recurring Functions

Assignment 4

Session 5 (1.5 hours)

  • 5.1 Assignment 4 review
  • 5.2 Anonymous Functions
  • 5.3 Sorting functions
  • 5.4 Introduction to main project

Assignment 5

Session 6 (1.5 hours)

  • 6.1 Assignment 5 review
  • 6.2 Converting between datatypes
  • 6.3 String Fomating
  • 6.4 Date Formatting
  • 6.5 Process User Input

Assignment 6

Session 7 (1.5 hours)

  • 7.1 Assignment 6 review
  • 7.2 File Processing
  • 7.3 Modules
  • 7.4 CSV Reader and Writer

Assignment 7

Session 8 (1.5 hours)

  • 8.1 Assignment 7 review
  • 8.2 Database Connectivity
  • 8.3 Integrate DB into main project

Assignment 8

Session 9 (1.5 hours)

  • 9.1 Assignment 8 review
  • 9.2 Try...except
  • 9.3 Fixing programming Errors
  • 9.4 Errors and Exceptions
  • 9.5 Logging

Assignment 9

Session 10 (1.5 hours)

  • 10.1 Assignment 9 review
  • 10.2 Numpy
  • 10.3 Setup environment

Assignment 10

Session 11 (1.5 hours)

  • 11.1 Assignment 10 review
  • 11.2 Pandas
  • 11.3 How to perform data Analysis 1

Assignment 11

Session 12 (1.5 hours)

  • 12.1 Assignment 11 review
  • 12.2 How to perform data Analysis 2
  • 12.3 Integrate Analytics into main project

Assignment 12

Session 13 (1.5 hours)

  • 13.1 Assignment 12 review
  • 13.2 API integration using 'requests'
  • 13.3 Web Scrapping

Assignment 13

Session 14 (1.5 hours)

  • 14.1 Assignment 13 review
  • 14.2 Visual Analytics uisng Bokeh

Assignment 14

Session 15 (1.5 hours)

  • 15.1 Assignment 14 review
  • 15.2 GUI using Tkinter

Assignment 15

Session 16 (1.5 hours)

  • 16.1 Assignment 15 review
  • 16.2 Intro to Machine Learning Apps
  • 16.3 Summary of the program

Assignment 16