Courses Details

Curriculum

Introduction

• Introduction to Programming
• Introduction to Python and How Python Works
• Introduction to Python Basic Course Structure
• How to install Python
• How to run Python Program using Command Line Window, IDLE, Notepad
• How to install Anaconda and run jupyter notebook for python

Getting Started

• Comments, Identifier, Reserved Words and Constant in Python
• Variable in Python
• Data Type in Python
• Declaring and Intializing Variables in Python
• Operators in Python
• Implicit and Explicit Type Conversion in Python
• Output Statement or Print Function in Python
• Getting input from user or Input Statement or input Function in Python
• Escape Sequence in Python

Conditional

• If Statement in Python
• Nested if Statement in Python
• if Statement with Logical Operator in Python
• Indentation in Python
• if else Statement in Python
• Nested if else Statement in Python
• if elif and if elif else Statement in Python

Loop

• range Function in Python
• For Loop and Nested for Loop in Python
• Enumerate() in Python with EXAMPLES
• While Loop and Nested while Loop in Python
• Break, Continue and Pass Statement in Python

String

• String in Python
• More on Strings(Access string using loop, repetitation and concatenation in string, mutable and immutable)
• String Formatting in Python
• String Methods in Python

List

• List in Python
• List methods in python
• More on Lists (Use loops with list, slicing in list, concatenation, repeatition, aliasing, copying and cloning in list)
• Nested List in Python

Tuple

• Tuple and tuple methods in Python
• More on Tuple(Use loops with tuple, slicing tuple, concatenation, repeatition, aliasing, copying tuple, getting user input as tuple, modifying and deleting tuple)
• Nested Tuple in Python

Set

• Set Type in Python
• Set methods in Python
• Nested Set in Python - FrozenSet

Dictionary

• Dictionary in Python
• Dictionary methods in Python
• More on Dictionary (Loop in Dictionary, Getting Dictionary input from user)
• Nested Dictionary in Python

Function

• Function and How Function Work in Python
• Arguments and its types in Python
• Local and Global Variable in Python
• global Keyword and function in Python
• Passing and returning List, Tuple, Set, Dictionary in Function
• Recursion in Python
• Anonymous Function or Lambda Expression in Python
• Function Decorator in Python

Ternary if and Comprehension

• Ternary if
• List, Tuple, Set and Dictionary Comprehension in Python
• Nested Comprehension in Python

Some Extra But Important Knowledge

• Generator Function Yield Statement and Next Function in Python
• Type and isinstance Function in Python
• Len,min,max and sorted Function
• Zip method
• Filter, map Function in Python
• Tips and Tricks in Python
• Getting Help in Python

Object Oriented Programming

• Class and Object in Python
• Constructor in Python
• Inheritance in Python
• Constructor in Inheritance
• Method Overloading, Overriding and Method with super in Python
• Special (Magic/Dunder) Methods

Exception Handling

• Exception Handling and Builtin Exception in Python
• User Defined Exception in Python
• Difference between Error and Exception and Warning in Python

VSCode and Virtual Environments

• Installing VSCode and coding in VSCode
• Debugging in VSCode
• Introduction to Virtual Environments
• Using conda and virtual environments with VSCode

Modules

• Module in Python, Math module in python
• Datetime Class in Python
• Random, sleep in Python
• Functools(Reduce and Memoization), getpass(getpass and getuser) and sys Module
• if __name__ == "__main__"

File Handling

• What is File and File Handling in Python
• Reading Files in Python
• Write Create Files in Python

Git and Github

• What is git/ What is Version control system?
• What is Github?
• How To Insatll Git
• Basic Commands: add, commit, push
• Undoing/Reverting/Resetting code changes
• Branches (Create, Merge, Delete)
• What is HEAD?
• .gitignore file
• Diff and Merge using vscode
• What is Pull Request?
• Brief intro to working with git, github with help of vscode and github desktop

Libraries and Projects

• Introduction to Libraries
• Introduction to Web Scrapping - Beautiful Soup
• Project 1 - Web scraping table from wikipedia
• PyQt Tutorial: Python GUI Designer
• Project 2 - Making a simple calculator
• Image Manipulation with Pillow
• Project 3 - Adding logo into Multiple images at once.

XML

• Data on the Web
• eXtensible Markup Language(XML)
• XML Schema
• Parsing XML

Working with JSON Data in Python

• JSON Introduction
• Encoding JSON Python Objects
• Decoding JSON Python Objects

Socket Programming in Python

• Connecting to a server
• A simple server-client program

SQLite3 with Python

• What is Database?
• Connect to Database in Python
• Create a Table
• Insert Record into Table
• Query and Fetchall
• Use the Where Clause

Introduction to Machine Learning

• Introduction to Machine Learning

Framing

• Key ML Terminology

Descending to ML

• Linear Regression
• Training  and Loss

Reducing Loss

• An alternative Approach
• Gradient Descent
• Learning Rate
• Optimizing Learning Rate
• Stochastic Gradient Descent

First Step with TF

• Toolkit

Generalization

• Peril of Overfitting

Training and Test Split

• Splitting Datat

Validation Set

• Another Partition

Representation

• Feature Engineering
• Qualities of good feature
• Cleaning Data

Feature Crosses

• Encoding Nonlinearity
• Crossing One Hot Vectors

Regularization : Simplicity

• L2 Regularization
• Lambda
• L2 Regularization Exercise

Logistic Regression

• Calculating a Probability
• Loss and Regularization

Classification

• Thresholding
• True vs False, Positive vs Negative
• Accuracy
• Precision and Recall
• ROC Curve and AOC
• Prediction Bias

Regularization: Sparsity

• L1 Regularization

Neural Networks

• Structure

Training with Neural Nets

• Best practices

Multi Class Neural Nets

• One vs All
• Softmax

Embeddings

• Motivation from collaborative filtering
• Categorical Input Data
• Translating to a Lower Dimensional Space
• Obtaining Embeddings

ML Engineering

• Production ML S
• Static vs Dynamic Training
• Static vs Dynamic Interface
• Data Dependencies
• Fairness
  • Types of Bias
  • Identifying Bias
  • Evaluating for Bias

ML System in Real World

• Cancer Prediction