Demo Videos

Course Highlights

    • 15+ Hours of Course Content
    • Covers Python & Jupyter Notebook
    • Expertise on Linear & Logistic Regression, Naive Bayes, Decision Tree
    • 1 Year Course Access
    • Instant Doubt Clarification
    • Telegram Developer Community
    • Real-world Capstone Project
    • Quizzes & Mini-projects
    • Certification of Completion
    • Become an Alumni of MicroDegree
    • *12+ hours uploaded. Fresh Course Content Updated Daily

Programming Languages and Tools Covered

Programming Languages and Tools Covered

  • Who Should Attend

    • Anybody interested in learning Machine Learning and Coding
    • Any Degree, Engineering & IT Students
    • Early Professionals
  • Job Opportunities

    • Machine Learning Engineer
    • AI Engineer
    • Data Analyst
    • Data Scientist
    • Data Engineer
    • ML Architect
    • Researcher - ML
    • Python Developer
    • Manager - Machine Learning

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

Join 3000+ Learners.

Learn coding and job-ready skills from industry experts in Kannada. MicroDegree is chosen among top innovative startups by Govt. of Karnataka's flagship Elevate-Call2 program

Snow
Forest

Join 3000+ Learners

Learn coding and job-ready skills from industry experts in Kannada. MicroDegree is chosen among top innovative startups by Govt. of Karnataka's flagship Elevate-Call2 program

Snow
Forest

Expert Instructor

 Chandan Adiga

ML Architect

Chandan Adiga is a Machine Learning expert with 10+ years of experience. He completed his M.Tech with Data Analytics specialization from BITS, Pilani - WILP program, and currently serves as an ML architect. He is also skilled at technologies spread across Android, iOS, MEAN stack, and ML/DL in his decade long IT career.

Chandan recommends learning AI & ML since the current technology trends are moving towards the world of automation. Having these relevant skills can give a head start to a potential career path across industries

 Darshan Adiga

Machine Learning Engineer at Datoin

Darshan Adiga is a Machine Learning Engineer and an NLP enthusiast. With an industry experience of more than 6 years, he has gained expertise in the field of Deep Learning, BigData & Distributed Systems. Throughout his ML journey, he has worked on Keras, PyTorch, TensorFlow, scikit-learn and other ML technologies.

He has been contributing to the field of ML and has published numerous research papers as well. With a particular interest in NLP, he has been working on enabling NLP solutions in Kannada Language using cutting-edge technologies.

Course curriculum

  • 1

    Basics

    • Welcome Message

    • Course Intro

    • What is Machine Learning

    • Applications of Machine Learning

    • Join Developer Community

    • AI vs Ml vs DL

    • Types of Learning

    • Machine Learning LifeCycle

    • Traditional Software Engineering vs Machine Learning

    • Basics Summary

    • Machine Learning Basics Quiz

    • Student Feedback - Fundamentals

  • 2

    Foundations

    • Python - Course Preview

    • Python - What is Python

    • Python - Who should Learn Python?

    • Python - Why Python?

    • Python - How to learn Python

    • Python - Basics Of Programming

    • Python - Installation & Setup

    • Python - My First Python Program

    • Python - Instruction Execution

    • Python - Variables

    • Python - Taking User Input

    • Python - Build Calculator Exercise

    • Python - Strings from Beginning

    • Python - String Manipulation

    • Python - Working With Numbers

    • Python - Intro to DataStructures

    • Python - Lists in Python

    • Python - List Methods

    • Python - Number List Manipulation

    • Python - Tuples

    • Python - If Else Statements

    • Python - Logical Operators

    • Python - Comparison Operators

    • Python - Build a Converter App

    • Python - Loops Intro

    • Python - While Loop

    • Python - Guessing Game Project

    • Python - For Loops In Python

    • Python - 2D Lists & Nested Loops

    • Python - Dictionaries

    • Python - Functions Intro

    • Python - Parameters in Functions

    • Python - Return Statements in Functions

    • Python - Word Counter Exercise

    • Python - Intermediate Project - Student Management System

    • Python - Handling Errors

    • Python - Generic Exceptions & Finally

    • Python - Modules

    • Python - Packages in Python

    • Python - File IO

    • Python - Object Oriented Programming (OOPs)

    • Python - Classes and Objects

    • Python - PyPI And Pip

    • Python - Coding Standards

    • Python - Price Tracker App - Intro

    • Python - Web Scraping Using Beautiful Soup

    • Python - Parsing Data

    • Python - Dynamic Multiple Inputs

    • Python - Price Check Logic

    • Python - Write Output File

    • Python - Project Wrap Up

    • Student Feedback - Python

    • Certification Instructions

    • 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

    • Assignment: Getting comfortable with Kaggle

    • Foundations - Kaggle quiz

    • 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

    • Assignment: Getting comfortable with pandas, numpy, matplotlib

    • Python recap quiz

    • Join Developer Community

    • Student Feedback - ML Basics

  • 3

    Intermediate

    • Intro to Linear Regression

    • Linear Regression - Understanding Data

    • Linear Regression - Loading Data

    • Linear Regression - Build & Test a Model

    • Linear Regression Quiz

    • 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

    • Student Feedback - Linear Regression

    • 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

  • 4

    Advanced

    • How ML Algorithms Learn - Part 1

    • How ML Algorithms Learn - Part 2

    • How ML Algorithms Learn - Part 3

    • Student Feedback - Logistic Regression

    • 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

    • Student Feedback - Naive Bayes

    • 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

    • Student Feedback - Decision Tree

  • 5

    Expert

    • Intro to Image Processing

  • 6

    Capstone Project

    • Intro to Capstone Project

    • Pipeline Of 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

    • What did you feel about the entire Course

    • Capstone Summary

  • 7

    Bonus

    • What to Learn Next

  • 8

    Certification

    • Project Intro

    • Project Option 1

    • Project Option 2

Learner Review

  • Sumedh Mallya

    All the courses are superb.. Especially Javascript course.. The tutor also teaches very good.. They respond to the queries quickly and are more supportive e.. They are sharing knowledge not behind money.. Because they teach as well as provide certificate for free I Javascript course.. Keep it up Microegree

  • Pushparaj Battemaru

    Java script course is really good course,I learnt lot about Java script from beginner level to intermediate level .This couse was really helped me a lot to learn new language in web development .The instructor was really good and his explaination style,voice (audio)and video clarity were crystal clear❤️.easily we can understand. In this course I learnt not only basics, it includes better parctical examples/around 3- 4 projects. And I will recommend you to take this course and it will help you to become a good developer. 🤝thank you microdegree for this great course🤝

  • 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.

  • RITHESHA G

    Learning In Kannada is a more effective way. So keep doing these type of courses..

  • Divya G

    Explaining in Kannada is understanding in good manner

  • Natesh S

    Doing a great job, Please continue it which helps many students.

  • Deepashree N

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

  • Darshan C

    Idea of teaching in kannada has helped me in understanding better

  • Usha

    Nicely explained by relating to practical examples

  • 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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New to MicroDegree?Steps to get MicroDegree Courses.

ಹೇಗೆ MicroDegree Course ಅನ್ನು ಪಡೆಯಬಹುದು ಎಂದು ಈ video ಮೂಲಕ, ಹಂತ ಹಂತಗಳಾಗಿ ವಿಸ್ತರಿಸಿದ್ದೇವೆ .ವೀಕ್ಷಿಸಿ ನಿಮ್ಮ ಮೆಚ್ಚುಗೆಯ courseನ್ನು ನಿಮ್ಮದಾಗಿಸಿ.

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New to MicroDegree?Steps to get MicroDegree Courses.

ಹೇಗೆ MicroDegree Course ಅನ್ನು ಪಡೆಯಬಹುದು ಎಂದು ಈ video ಮೂಲಕ, ಹಂತ ಹಂತಗಳಾಗಿ ವಿಸ್ತರಿಸಿದ್ದೇವೆ .ವೀಕ್ಷಿಸಿ ನಿಮ್ಮ ಮೆಚ್ಚುಗೆಯ courseನ್ನು ನಿಮ್ಮದಾಗಿಸಿ.

Frequently Asked Questions

  • Who should Sign up?

    Anybody willing to learn Programming in a simple way could sign up. Students starting from the High School, Pre-University, Diploma, Engineering, Graduates, Freshers, Early Professional and even Experienced Professionals. Our Courses are designed keeping in mind to give clarity on programming foundations to move up to expert level irrespective of educational backgrounds.

  • Will I get a Certificate?

    Yes, you will get an e-Certificate of Completion once you successfully finish all the modules within your course. We track individual progress reports which includes micro lessons, quizzes, assignments etc.

  • Will I have to complete or submit any projects to get the Certification?

    No, you don't have to complete or submit any major projects to get an e-Certificate. Although, Courses include minor quizzes, assignments and take away projects for which 'Source Codes' would be shared by MicroDegree.

  • What is the duration to complete Courses?

    While you will have a life-time access to complete the courses, we recommend you to complete the courses by a month's time for better learning outcomes.

  • How can I get my Doubts clarified?

    You would be using our ' Discord Community' for instant doubt clarifications and also weekly 'Mentorship' is done through free webinars on respective courses by our expert educators.