AI and Machine Learning

ClusterPhi
Last Update September 6, 2022

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.

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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

ClusterPhi

4.0/5
18 Courses
1 Review
96 Students
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Free
Level
All Levels
Lectures
70 lectures
Language
English

Material Includes

  • Course Material
  • Guided Path
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