Course Highlights

    • Live Doubt Clarification
    • 04:00 PM to 06:00 PM (Saturday - Sunday)
    • Concepts Explained in Kannada
    • Completion Certificate
    • Build Real-World Projects
    • Interview Preparation
    • Career Assistance
  • Job Opportunities

    • Working Professionals
    • Students & Freshers
    • Business Analyst
    • Data Analyst
    • Data Scientists
    • Visualization Engineer
    • Power BI Developer

Course curriculum

  • 1

    Python

    • What is Python

    • Who should Learn Python?

    • Why Python

    • How to learn Python

    • Basics Of Programming

    • Python Installation & Setup

    • My First Python Program

    • Instruction Execution in Python

    • Variables

    • Taking User Input

    • Build Calculator Exercise

    • Strings from Beginning

    • String Manipulation

    • Working With Numbers

    • Intro to DataStructures

    • Lists in Python

    • List Methods

    • Number List Manipulation

    • Tuples

    • If Else Statements

    • Logical Operators

    • Comparison Operators

    • Build a Converter App

    • Loops Intro

    • While Loop

    • Guessing Game Project

    • For Loops In Python

    • 2D Lists & Nested Loops

    • Dictionaries

    • Functions Intro

    • Parameters in Functions

    • Return Statements in Functions

    • Word Counter Exercise

    • Intermediate Project - Student Management System

    • Handling Errors

    • Generic Exceptions & Finally

    • Modules

    • Packages in Python

    • File IO

    • Object Oriented Programming (OOPs)

    • Classes and Objects

    • PyPI And Pip

    • Coding Standards

    • Price Tracker App - Intro

    • Price Tracker App - Intro

    • Web Scraping Using Beautiful Soup

    • Parsing Data

    • Dynamic Multiple Inputs

    • Price Check Logic

    • Write Output File

    • Project Wrap Up

    • Python Career Path

  • 2

    SQL

    • Welcome to this course

    • What is Database?

    • Installing MySQL

    • Alternative Mysql Installation

    • Xampp-2

    • Creating a database

    • Creating first table

    • Insert Value to table

    • Select statement

    • logical AND and OR

    • BETWEEN and NOT Operator

    • Primary Key, Default and Null

    • Customers table

    • Testing the customer table

    • Answering questions

    • Getting specific data

    • Updating the customers table

    • Deleting the customers table

    • Aggregate Functions

    • CONCAT()

    • REPLACE()

    • SUBSTRING()

    • CHAR_LENGTH()

    • UPPER()

    • Look into Distinct

    • ORDER BY

    • LIMIT

    • Pattern Matching

    • COUNT()

    • GROUP BY

    • MIN MAX and SUBQUERIES

    • GROUP BY with MAX and MIN

    • SUM and AVG

    • having

    • foreign key

    • largedataset

    • Data types Integer and String

    • DATE, DATETIME and JSON

    • date time code

    • let's Join

    • Types of JOINS

    • INNER JOIN

    • Relationships in MYSQL

    • join 3 tables

    • LEFT JOIN

    • Right Join

    • OUTER JOINS & UNIONS

    • Views

    • Indexes

    • Assignment Info

  • 3

    Data Analytics

    • What is Data Analytics

    • Applications Of Data Analytics

    • Steps in Data Science

    • Career Roles in Data Science Field

    • Tools For Data Science

    • Why Pandas?

    • Reading Data and Iterate through each Row

    • Description of data and sorting

    • Saving Data

    • Filtering Data, Reset Index, Regex Filtering and Conditional Changes

    • Aggregate Statistics using Groupby

    • Working with huge data

    • The Basics of Numpy

    • Accessing Specific Elements

    • Initializing Different Arrays

    • Basic Mathematics, Statistics and Linear Algebra

    • Reorganizing Arrays & copy variable

    • Load data, Advanced Indexing and Boolean Masking

    • Data Visualization - What is MatPlotLib?

    • Data Visualization - Line Graphs and ShortHand Notations

    • Data Visualization - Bar Graphs in MatPlotLib

    • Data Cleaning - Introduction, Data & Null Values

    • Data Cleaning - Removing Column and Rows

    • Data Cleaning - Normalizing Data

    • Capstone Project Part-1

    • Capstone Project Part-2

    • Capstone Project Part-3

    • Capstone Project Part-4

    • Capstone Project Part-5

    • Capstone Project Part-6

  • 4

    Artificial Intelligence & Machine Learning

    • What is Machine Learning

    • Applications of Machine Learning

    • AI vs Ml vs DL

    • Types of Learning

    • Machine Learning LifeCycle

    • Traditional Software Engineering vs Machine Learning

    • Basics Summary

    • Jupyter Notebook Setup

    • Google Colab - Intro & Basic Setup

    • DataSet - What, Where , How

    • Kaggle Intro

    • Kaggle - Building a Profile

    • Kaggle - Working with Notebooks

    • Kaggle - Sharing a Notebook

    • Kaggle - Dataset Upload

    • Kaggle - Link Dataset to Notebook

    • Python Fundamentals Recap

    • Python Recap Installing Library

    • Data Visualization using Python - Intro to Matplotlib

    • Intro to Numpy in Python

    • Intro to Pandas in Python

    • Intro to PIL/OpenCV

    • ML Frameworks - Intro to Scikit-learn, TensorFlow, Pytorch

    • Intro to Linear Regression

    • Linear Regression - Understanding Data

    • Linear Regression - Loading Data

    • Linear Regression - Build & Test a Model

    • Linear Regression - Finding Linearity

    • Linear Regression - Understanding Linear Function and Slope

    • Linear Regression - Merging Math Line & Training Data

    • Linear Regression - Manual Training Line of Best Fit Regression Line

    • Linear Regression - Root Mean Squared Error

    • Linear Regression - Inferencing

    • Linear Regression - Coefficient & Intercept

    • Linear Regression - Bias & Variance

    • Linear Regression - UnderFitting vs Overfitting

    • Linear Regression Summary

    • Logistic Regression Intro

    • Logistic Regression - Data Setup

    • Logistic Regression - Data Cleanup & Feature Engineering - Part 1

    • Logistic Regression - Data Cleanup & Feature Engineering - Part 2

    • Logistic Regression - Data Cleanup & Feature Engineering - Part 3

    • Logistic Regression - Predicting Future Tips Data - Part 1

    • Logistic Regression - Predicting Future Tips Data - Part 2

    • Logistic Regression - Predicting Future Tips Data - Part 3

    • Logistic Regression - Predicting Future Tips Data - Part 4

    • Logistic Regression - Predicting Future Tips Data - Part 5

    • Logistic Regression - Theoretical Understanding - Part 1

    • Logistic Regression - Theoretical Understanding - Part 2

    • Logistic Regression - Theoretical Understanding - Part 3

    • Logistic Regression Summary

    • Intro to Linear Regression

    • How ML Algorithms Learn - Part 1

    • How ML Algorithms Learn - Part 2

    • How ML Algorithms Learn - Part 3

    • Naive Bayes - Intro

    • Naive Bayes - Classification vs Regression

    • Naive Bayes - What is Customer Segmentation

    • Naive Bayes - Data Cleanup And Feature Engineering

    • Naive Bayes - Train & Test

    • Naive Bayes - Confusion Matrix

    • Naive Bayes - How it Works?

    • Naive Bayes - Summary

    • Decision Tree - Overview

    • Decision Tree - Understanding DataSet

    • Using Decision Tree

    • What is Decision Tree

    • How To Use Decision Tree

    • How to Use Decision Tree Continued

    • Decision Tree - Genie Impurity

    • Visualize Decision Tree Model

    • Random Forest

    • Decision Tree - Summary

    • Intro to Image Processing

    • Convert Image Data to Features - Part 1

    • Convert Image Data to Features - Part 2

    • Train & Evaluate Model

    • Model Saving & End-To-End Prediction

    • Capstone Summary

    • What to Learn Next

    • Project Intro

    • Project Option 1

    • Project Option 2

  • 5

    Power BI

    • Power BI Live -Day 01

    • Power BI Live -Day 02

    • Power BI Live - DAY 03

    • Power BI Live - Day 04

    • Power BI Live - Day 05

    • Power BI Live -Day 06

    • Power BI Live -Day 07

    • Power BI Live -Day 08

    • Power BI Live -Day 09

    • Power BI Live -Day 10

    • Power BI Live -Day 11

    • Power BI Live -Day 12

    • Power BI Live -Day 13

    • Power BI Live -Day 14

    • Power BI Live -Day 15

    • Power BI Live -Day 16

    • Power BI Live -Day 17

    • Power BI Live -Day 18

    • Power BI Live -Day 19

    • Power BI Live -Day 20

    • Power BI Live -Day 21

    • Power BI Live - Day 22

    • Power BI Live -Day 23

    • Power BI Live -Day 24

    • Power BI Live - Day 25

    • Power BI Live -Day 26

    • Power BI Live -Day 27

    • Power BI Live -Day 28

    • Power BI Live -Day 29

    • Power BI Live-Day 30

    • Power BI Live -Day 31

    • Power BI Live -Day 32

    • Power BI Live - Day 33

  • 6

    AWS

    • Introduction

    • Account Setup and networking basics

    • VPC Basics with IGW Hands On

    • Private and Public Subnet ,Bastion Host ,NAT Gateway

    • Security Groups Vs NACL , VPC Peering Hands On

    • VPC peering types with limitations on transitive peering and revision on

    • AWS Transit gateway , vpc project

    • AWS Hands-on TGW , CA-TGW

    • AWS VPC Project Explanation , IAM Introduction

    • AWS Roles , CLI User Demo , IAM Cross Account Access Hands On

    • IAM Hands on Projects

    • EC2 introduction , EC2 hands on

    • EC2 Lifecycle , EBS Snapshots Hands-On

    • Create Image , Tomcat server Installation

    • AWS Backup , AWS SNAPSHOTS , LCM HANDS ON , LOAD BALANCERS Day-15

    • Application load balancer Hands-On - Part 1

    • Application load balancer Hands-On - Part 2

    • Autoscaling Hands-On

    • S3 Buckets - Part 1

    • S3 Buckets - Part 2

    • Route 53

    • Building Static Website

    • Relational Database Service(RDS)

    • Server less Architecture

  • 7

    DevOps

    • DevOps Day 01()

    • DevOps Git Introduction Day-02

    • DevOps Git Architecture Day-04

    • DevOps Git Branching Day-05

    • DevOps Overview of Git Day-06

    • DevOps Git Merge , Stash , Conflicts Day-07

    • DevOps AWS Assignment Solution Day-08

    • DevOps Maven Part 01 Day-09

    • DevOps Maven Part 02 Day-10

    • DevOps Maven Part 03 Day-11

    • DevOps Jenkins Introduction Day-12

    • DevOps Jenkins Part 2 Day-13

    • DevOps Jenkins Part 3 Day-14

    • DevOps Day-15

    • DevOps Ansible part 1 Day-16

    • DevOps Day-17

    • DevOps Day-18

    • DevOps Day-19

    • DevOps Day-20

    • DevOps Day-21

    • DevOps Day-22

    • AWS & DevOps Resume Building Session

    • DevOps Project

Placement success stories

Sudeep Dsouza


Associate Software developer
Mindstack Technologies

Samanth Kumar


Associate Software developer
Mindstack Technologies

Kavya S N


Associate Software developer
Mindstack Technologies

Manjunath


Junior Software developer
Cliq Labs

Deeraj R


Junior Software developer
Cliq Labs

Ashwath


Software Trainee
7Edge Technologies

Placement success stories

Sudeep Dsouza


Associate Software developer
Mindstack Technologies

Samanth Kumar


Associate Software developer
Mindstack Technologies

Kavya S N


Associate Software developer
Mindstack Technologies

Manjunath


Junior Software developer
Cliq Labs

Deeraj R


Junior Software developer
Cliq Labs

Ashwath


Software Trainee
7Edge Technologies

Completion Certificate by MicroDegree

On completion of course become a proud alumni of MicroDegree. MicroDegree is chosen among top innovative startups by Government of Karnataka's flagship Elevate Call-2 program

Learner Review

  • Akshata Kothari

    Thank you so much for this course. The concepts explained by the trainer was really good and clear. As it was in kannada it helped me in understanding the concept better.

  • karthik k

    You are giving examples for every concept which makes us learn faster. Excellent. Keep going

  • Chethana Amin

    It's really a good thought to start a course in kannada. It helps lot of people.

  • Divya G

    Explaining in Kannada is understanding in good manner

  • Deepashree N

    Awesome thing... u guys made python very very easy which can be learnt in our mother tongue.... thank you...

  • Monica Govindappa

    Learning in Kannada is helping out to grasp things quickly over all making it to learn in an interesting way.

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