Course curriculum

  • 1

    Student Guide Book

    • Student Guide Book

    • Schedule/curriculum Time Table
  • 2

    Introduction Python - Pre - Learning Session

    • Python Crash course Introduction

    • python Demo n install

    • Python Intro and Installation

    • Basic python and datatype

    • Basic,Number,string

    • Data types
  • 3

    chapter 1 - Control flow

    • If else conditions

    • While & for loop conditions

  • 4

    chapter -2 Deep Learning

    • 01_Logistic Regression vs DL

    • TesorFlow and Keras
  • 5

    Chapter 3 - Exception Handling

    • Exception Handling
  • 6

    chapter 4 -Functions

    • Functions
  • 7

    Chapter 5 - OOPS

    • CLASSES

    • OOP
  • 8

    Chapter -6 Libraries

    • Introduction to Libraries

    • Library Introduction

    • Matplolib

    • Numpy

    • Pandas
  • 9

    Chapter 7 - Mathematics

    • Data

    • Linear Algebra

    • Statistics

    • stats - probs
  • 10

    Chapter 8 - Machine Learning Models

    • clustering

    • Clustering

    • Evaluation Metrics

    • Logistic Regression - Feature Regression

    • Logistic Regression

    • Linear And Logistic

    • Simple Linear regression

    • Multiple Linear regression
  • 11

    Zoom Live Session Links

    • Data Science _1st Live Session _06th July 2021 _ 6:00 pm

    • Data Science _2nd Live Session _Jul 8, 2021 06:00 PM

    • Data Science _3rd Live Session _Jul 10, 2021 06:00 PM

    • Data Science _4th Live Session _Jul 13, 2021 06:00 PM

    • Data Science _5th Live Session _Jul 15, 2021 06:00 PM

    • Data Science _6th Live Session _Jul 17, 2021 06:00 PM

    • Data Science _7th Live Session _Jul 20, 2021 06:00 PM

    • Data Science _8th Live Session _Jul 22, 2021 06:00 PM

    • Data Science _9th Live Session _Jul 24, 2021 06:00 PM

    • Data Science _10th Live Session _Jul 27, 2021 06:00 PM

    • Data Science _11th Live Session _Jul 29, 2021 06:00 PM

    • Data Science _12th Live Session _Jul 31, 2021 06:00 PM

    • Data Science _13th Live Session _Aug 03, 2021 06:00 PM

    • Data Science _14th Live Session _Aug 05, 2021 06:00 PM

    • Data Science _15th Live Session_ Aug 7, 2021 06:00 PM

    • Data Science _16th Live Session_ Aug 10, 2021 06:00 PM

    • Data Science _17th Live Session_ Aug 12, 2021 06:00 PM

    • Data Science _18th Live Session_ Aug 14, 2021 06:00 PM Cancelled

    • Data Science _18th Live Session_ Aug 17, 2021 06:00 PM

    • Data Science _19th Live Session_ Aug 18, 2021 06:00 PM

    • Data Science _20th Live Session_ Aug 19, 2021 06:00 PM

    • Data Science_21st Live Session_ Aug 20, 2021 06:00 PM

    • Data Science_22nd Live Session_ Aug 23, 2021 06:00 PM

    • Data Science_23rd Live Session_ Aug 24, 2021 06:00 PM
  • 12

    Major Project

    • Wireless Sound Control

    • Major Project Submission
  • 13

    Live Project Instructions

    • Orientation Meeting_Live Industrial Project
  • 14

    Internship Project 1 - Linear discriminant analysis

    • Part-1

    • Mnist Project
  • 15

    Internship project -2 _Hierarchical Clustering

    • Part-1

    • Part-2

    • Data Set
  • 16

    Internship Project Live Sessions

    • Project 1 - Hand Written Digit Prediction

    • Project -2 _Hierarchical Clustering

    • Internship Project Submissions

    • Orientation meeting

  • 17

    Module 1: Installing and Starting Python

    • 1.1: Overview

    • 1.2: Installing Python

    • 1.3: Interactive Python

    • 1.4: Significant Whitespace

    • 1.5: Python Culture

    • 1.6: The Python Standard Library

    • 1.7: Summary
  • 18

    Module 2: Scalar Types, Operators and Control Flows

    • 2.1: Overview

    • 2.2: Relational Operators

    • 2.3: Control Flow

    • 2.4: While Loops

    • 2.5: Summary

    • Scalar Type Operators and Control Flow Slides
  • 19

    Module 3: Introducing Strings, Collections and Iterations

    • 3.1: Overview

    • 3.2: String

    • 3.3: String Literals

    • 3.4: Bytes

    • 3.5: List

    • 3.6: Dictionary

    • 3.7: For Loop

    • 3.8: Putting It All Together

    • 3.9: Summary
  • 20

    Module 4: Modularity

    • 4.1: Overview

    • 4.2: Modules

    • 4.3: Functions

    • 4.4: Name

    • 4.5: The Execution Model

    • 4.6: Command Line Arguments

    • 4.7: Docstrings

    • 4.8: Comments

    • 4.9: Shebang

    • 4.10: Summary

    • Modularity Slides
  • 21

    Module 5: Objects and Types

    • 5.1: Overview

    • 5.2: Passing Arguments and Returning Values

    • 5.3: Function Arguments

    • 5.4: Python's Type System

    • 5.5: Scopes

    • 5.6: Everything is an Object

    • 5.7: Summary

    • Objects and Types
  • 22

    Module 6: Built-in Collections

    • 6.1: Overview

    • 6.2: Tuples

    • 6.3: Strings

    • 6.4: Ranges

    • 6.5: Lists

    • 6.6: Dictionaries

    • 6.7: Sets

    • 6.8: Protocols

    • 6.9: Summary

    • Built-in Collections Slides

    • Codes for Built-in Collections

  • 23

    Module 7: Exceptions

    • 7.1: Overview

    • 7.2: Exceptions and Control Flow

    • 7.3: Handling Exceptions

    • 7.4: Exceptions and Programmer Errors

    • 7.5: Re-raising Exceptions

    • 7.6: Exceptions and Part of the API

    • 7.7: Exceptions and Protocols

    • 7.8: Avoid Explicit Type Checks

    • 7.9: It's Easier to Ask Forgiveness Than Permission

    • 7.10: Cleanup Actions

    • 7.11: Platform Specific Code

    • 7.12: Summary

    • Exceptions Slide
  • 24

    Module 8: Iterations and Iterables

    • 8.1 Overview

    • 8.2: List and Set Comprehensions

    • 8.3: Dictionary Comprehensions

    • 8.4: Filtering Comprehensions

    • 8.5: Iteration Protocols

    • 8.6: Generator Functions

    • 8.7: Maintaining State in Generators

    • 8.8: Laziness and the Infinite

    • 8.9: Generator Expressions

    • 8.10: Iteration Tools

    • 8.11: Summary

    • Iteration and Iterables Slides
  • 25

    Module 9: Classes

    • 9.1: Overview

    • 9.2: Classes

    • 9.3: Defining Classes

    • 9.4: Instance Methods

    • 9.5: Instance Initializers

    • 9.6: A Second Class

    • 9.7: Collaborating Classes

    • 9.8: Booking Seats

    • 9.9: Methods for Implementation Details

    • 9.10: Object Oriented Design with Function Objects

    • 9.11: Polymorphism and Duck Typing

    • 9.12: Inheritance and Implementation Sharing

    • 9.13: Summary

    • Classes Slides
  • 26

    Module 10: File IO and Resource Managements

    • 10.1: Overview

    • 10.2: Opening Files

    • 10.3: Writing Text

    • 10.4: Reading Text

    • 10.5: Appending Text

    • 10.6: Iterating Over Files

    • 10.7: Closing Files with Finally

    • 10.8: With Blocks

    • 10.9: Binary Files

    • 10.10: Bitwise Operators

    • 10.11: Pixel Data

    • 10.12: Reading Binary Data

    • 10.13: File-like Objects

    • 10.14: Context Manager

    • 10.15: Summary

    • MTA Exam Objectives