About This Course
Machine learning (ML) involves computer algorithms to automatically improve the performance
through the use of data and experience. It is a part of AI.
Learning Objectives
- Quickly recognize trends and patterns
- Eliminating manual intervention (automation)
- Enhancing consistently
- Taking care of multidimensional data and apps
Material Includes
- Course Material
- Guided Path
Requirements
- A bachelor’s degree with an average of 50% or higher marks
- Basic understanding of programming concepts and mathematics
- Working Professionals.
Target Audience
- Graduate Students
- Working Professionals
Curriculum
70 Lessons
Pre-Program Preparatory Content
Introduction to Python
Python for Data Science
Data Visualization in Python
Data Analysis Using SQL (Optional)
Advanced SQL and Best Practices (Optional)
Data Analysis in Excel
Analytics Problem Solving
Math for Machine Learning
Statistics and Exploratory Data Analytics
Machine Learning – I
Machine Learning – II
Deep Learning
Natural Language Processing
ELective 1: DL with MLops
Elective 2: NLP with Mlops
Elective 3: AI strategy
Capstone
Reinforcement Learning (Optional)
Your Instructors
