All Courses
Login/ Sign up
Get started

By signing up, you agree to our Terms of Use and Privacy Policy.
Reset your password
Enter your email and we'll send you instructions on how to reset your password.

Request a Quote

We value your privacy. We will never spam you.

Machine Learning Training Course

5
(59 Ratings)
132
Students Enrolled

In collaboration with IBM, Greycampus presents a comprehensive Machine Learning training course that covers Python, Supervised and Unsupervised Learning, Recommender Systems and many more industry-specific techniques and strategies of Machine Learning. Developed by industry experts, this course will bring you up to pace on all the strategies and tools that ML engineers incorporate in their work on a day-to-day basis.

TL;DR

Highly interactive Instructor-led Training

2 Projects to provide hands-on experience

Teaching assistance to support your learning journey

Course Overview

Machine learning is a form of artificial intelligence where the focus is to develop computer programs that automate data analysis by learning and adapting through the experience without the need for precise programming. Our course has been designed to help you master machine learning concepts and techniques working with actual data, developing algorithms through supervised and unsupervised learning, performing classification and regression operations and constructing time series models. This course explores in depth the libraries and functionalities the python programming language offers for machine learning techniques in order to draw conclusions from data. The course includes 2 projects to solidify your knowledge and skills you've gained.

schedules timings location

Customized training available. Contact us at sales@greycampus.com

Course Curriculum

  • Introduction to Artificial Intelligence and Machine Learning
  • Data Wrangling and Manipulation
  • Supervised Learning
  • Feature Engineering
  • Supervised Learning
  • Unsupervised Learning

What You Get

1. 30 hours spread across 8 days of highly interactive Instructor-led Training

2. 12 hours of self-paced learning

3. 2 projects to provide hands-on training

4. Teaching assistance to support your learning journey

5. Learn the required skills using Jupyter Notebook web application

Dual Certification

  • Machine Learning Sample Certificate

    IBM Certification
  • Machine Learning Sample Certificate

    Course Completion Certificate from GreyCampus

Boost your career. Get certified.

  • Our Course Advisor

     

    Rajeev Kumar is a highly optimistic individual that has worked with Fortune 100 clients including Google, IBM, and Disney. With over 22 over years of experience in the IT industry, Rajeev has turned his focus for the past 5 years towards Data Science and AI/ML. To this end, he has come up with Data Science and AI/ML backed solutions in various fields, from Fashion to Education. His solutions have saved millions of dollars on costs to his clients.

    Rajeev is committed to sharing his learnings with enterprises to build Data Science and AI capabilities for their domains to make exponential gains.

    Rajeev Kumar

Prerequisites

The prerequisite for this Machine Learning course is a basic understanding of mathematics and statistics at a graduate level. The learner should have an understanding of Python for Data Science and Statistics essential for Data Science, for a better understanding of the Machine Learning course.

Reviews

"The project work really nailed what I learnt in the online classes. I recommend taking the project work they provide seriously."

- Kevin Johnson

"I really like the fact that I can do the self paced content over the week and then take up the instructor classes at the weekend."

- Jeanne Turner

"It took a lot of effort and dedication but I'm so happy that I put in the effort. Switching careers paid off as I just landed a AI/ML statistician job! Good job guys!"

- Angela Webb

FAQ

  • What is Machine Learning?

    Machine learning works on bringing together statistics and computer science to enable computers to learn how to do a given task without being programmed to do so. It focuses on the designing of the system, thereby allowing them to learn and derive meaning from all the available data. The goal is to allow machines to learn and adapt without human intervention.

  • What is the duration of this course?

    • 30 Hours spread across 8 days of highly interactive Instructor-led Training

    • 12 Hours of Self-paced learning

     

  • How many projects are included in this course?

    This course includes 2 hands-on projects to put it into practice what you learn throughout the course.

Download full course agenda/brochure