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Course Overview

This course is the perfect place for beginners to understand the core idea of building systems that have the ability to automatically learn from data and improve the experience without being explicitly programmed. In this course, you will learn about concepts of Machine Learning, effective machine learning techniques, and gain practice implementing them and getting them to work for yourself all in a classroom program. The course will be mentored & guided by Industry experts having hands-on experience in ML-based industry projects. The course includes 1 major & 2 minor projects based on real-world applications with guided lab sessions.

It will be an online live (Live Stream) class, so you can attend this class from any geographical location. It will be an interactive live session, where you can ask your doubts to the instructor (similar to offline classroom program).


Classes will be scheduled for Weekends - Saturday & Sunday
Class timing would be 4 PM - 7 PM (IST)

Pre-requisites:
Should know the basics of any one programming language: C / C++, Java or Python
Recommended for:
Anyone who wants to learn and build ML-based solutions specifically

  • College students who are looking for training in Machine Learning
  • Working Professionals who want to learn machine learning concepts.

Course Features

  • Training Certificate
  • Limited Batch Strength - 25
  • Complimentary access to ML basics course worth Rs 1499
  • 6 months access to recorded Live lectures of this course
  • Project-based learning which will add stars to your resume 
  • 3 projects based on real-world applications
    • 1 Major Project
    • 2 Minor Projects
  • Understanding of how data scientists work on Kaggle

What You Will Learn

  • Python Tools related to Data Science
  • Machine Learning
  • Application of ML Models to solve real life problems
  • Kaggle

Course Content

  Lecture 1

  • What is Machine Learning

  • Type of problems solved by ML

  • Real-World Scenario where ML is applicable

  • Software Installation

  • Brief Discussion about Libraries and application

  Lecture 2

  • Hands-on Python

  • Basic Syntax and data structures

  • Knowledge about NumPy

  Lecture 3

  • Learning Data Handling in Pandas

  • Understanding different Graphs in Matplotlib

  • Understanding of -

    • Categorical Data

    • Data Scaling

    • Data Splitting

    • Handling Missing Data

  Lecture 4

  • Linear Regression Intuition

  • A-Z Mathematical Explanation to LR

    • Model

    • Forward Propagation

    • Cost Function

    • Gradient Descent

    • Training

  • Linear Regression Scratch Code

  Lecture 5

  • Linear Regression using library

  • Multiple Linear Regression

  • Polynomial Regression

  • Evaluation Metrics

  Lecture 6

  • Support Vector Regression

  • Decision Tree Regression

  • Random Forest Regression

Show More

Course Mentors


Mohit Gupta (Instructor)

MS in Data Science @ Monash University, Australia | ML Engineer @ GeeksforGeeks


Grad Student at Monash University, Australia with subjects focused on Machine Learning, Natural Language Processing, Data Science, Big Data. He is actively working in research and has published research papers in the field of neural networks, forecasting, and image processing. He has experience of being a technical coordinator in Google Developers Group. He has also worked as a research intern at the Indian Institute of Technology (IIT Jammu). He has been working on ML ( as an intern + Full-time)  for the last 3.5 years.


FAQs

  1. Is there any number to contact for any query?
    You may call us on our toll-free number: 18001238622  or Drop us an email at geeks.classes@geeksforgeeks.org
     
  2. How will we work on the projects?
    You will begin the project with the help of course mentors. Each student will be guided by the mentor in the class itself.
     
  3. Is this a certification course?
    Yes, It's a GeeksforGeeks certified program that includes projects along with learning. All students will receive a Training certificate with appropriate grades.
     
  4. What is the size of a batch?
    The planned batch size is 25.
     
  5. How can I register for the course?
    Click on the Signup for free button & Pay Fees online
     
  6. What is the course duration?
    The course includes 12 lectures which will be completed in 6 weeks.
     
  7.  What is the duration of the class?
    The class duration is 3 Hours (4 - 7 pm IST). Classes are scheduled for Saturdays & Sundays.

Course Registration

Previous Batches

Batch Date Type Register
MLPL 6 03 April '21 to 09 May '21 Live Classes
Registration Closed