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Machine Learning

Explore the fundamentals of Machine Learning in this comprehensive course. Learn about various ML types such as Regression, Classification, Ensemble Methods, and Clustering. Understand essential concepts like Feature Engineering (FE) and Hyperparameter Optimization (HPO), with practical use cases. Perfect for beginners looking to build a strong foundation in machine learning techniques and real-world applications.

Satyajit Pattnaik

Expert in Generative AI, ML, NLP & Data Engineering

Here’s what you will learn?

  • Understanding ML Concepts
  • Hands-on Model Development
  • Data Preprocessing & Feature Engineering
  • Algorithm Implementation
  • Preparation for Advanced AI/ML

This Course Includes

  • Recorded Lessons:  86
  • Recorded Hours:  20hr 13min
  • Certificate of completion
  • Access on Mobile

Course Description

Machine Learning (ML) is a subset of Artificial Intelligence (AI) that focuses on building algorithms and models that enable computers to learn patterns from data and improve their performance over time without being explicitly programmed. 

It involves various techniques, including supervised learning, unsupervised learning, and reinforcement learning, to solve real-world problems such as image recognition, natural language processing, recommendation systems, and predictive analytics. Machine Learning applications span across industries like healthcare, finance, e-commerce, and autonomous systems, making it a crucial technology in today's data-driven world.

Course Content

86 Lessons | 20hr 13min

About the instructor
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Satyajit Pattnaik

Expert in Generative AI, ML, NLP & Data Engineering

Satyajit Pattnaik has 13+ years of experience in AI, Data Analytics, and Data Science across industries such as telecom, cybersecurity, insurance, and e-commerce. With over a decade of training and teaching experience, he has conducted numerous sessions on Data Science, ML, and AI. He has also been a keynote speaker at international conferences and universities across the APAC region.

Frequently Asked Questions

Basic knowledge of programming (preferably Python), statistics, and linear algebra is recommended. Familiarity with concepts like algorithms and data structures will be beneficial.

Yes, programming skills are essential, especially in Python, as it is one of the most popular languages used in Machine Learning. We will guide you through the relevant coding skills during the course.

Introduction of Machine Learning, Regression, Classification, Ensemble, Clustering and many more.

This course is designed for beginners who have a basic understanding of programming. We will cover the fundamentals of machine learning and progressively move to more advanced concepts.

The duration of the course varies depending on the learning pace.
Machine Learning
(4.3)
20hr 13min
₹999 ₹1299
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