Foundations of Data Science (AI/ML): The Big PictureFree

What you'll be able to do

• Understand what is Machine Learning
• Understand real world applications of ML
• Know commercially viable ML projects in each function
• Get familiar with ML terminologies
• Get a sense of how ML model is built and evaluated
• Understand different types of ML problems
• Gain knowledge of popular ML algorithms

1. 01Introduction to ML13 lessons · 1 h 5 min

   1. Welcome Message (Don't Skip!)1:00
   2. What is Machine LearningPreview7:11
   3. How to Get Queries ResolvedPreview1:00
   4. Garbage-In Garbage-OutPreview5:38
   5. Broad Types of ML Problems Part-1Preview1:56
   6. Broad Types of ML Problems Part-23:58
   7. Broad Types of ML Problems Part-34:07
   8. Marketing and Sales Use CasesPreview11:57
   9. Logistics & Production, HR, Customer Support Use CasesPreview7:53
   10. Course Review1:00
   11. What ML Can and Cannot Do7:34
   12. Data Science vs ML vs AI vs Deep Learning vs Statistical Modeling8:04
   13. Quiz - Introduction to ML4:00
2. 02ML Project Workflow6 lessons · 23 min

   1. Introduction to ML Project WorkflowPreview5:53
   2. DiscoverPreview4:36
   3. DesignPreview4:16
   4. DevelopPreview2:10
   5. TestingPreview2:19
   6. DeployPreview3:48
3. 03ML Models & Terminology8 lessons · 36 min

   1. Interpreting ML Models3:01
   2. Interpreting ML Models Part-16:00
   3. Interpreting ML Models Part-23:01
   4. How to Validate ML Models6:17
   5. Need for Validation Sample3:51
   6. ML Terminology You Need to Know - Part 1 - Supervised vs Unsupervised Learning6:25
   7. ML Terminology You Need to Know - Part 2 - Independent vs Dependent Variables3:32
   8. ML Terminology You Need to Know - Part 3 - More Terms4:06
4. 04Special Applications6 lessons · 26 min

   1. What is Ensemble Learning4:35
   2. Reinforcement Learning Intuition4:51
   3. Basic Statistical Concepts Part-16:58
   4. Basic Statistical Concepts Part-23:52
   5. Role of Significance Tests4:22
   6. Course Review1:00

What you need

• Basic Maths and Logical Reasoning
• Curiosity about Data Science
• Learning Mindset

Who this course is for

• Future Data Scientists and ML Engineers
• Product Managers, Program Managers, Scrum Masters working in ML/Data science project
• Software/Data engineers interested in quantitative analysis
• Software engineers interfacing with data science team
• Executives who have to lead or interact with Data Scientists

Your instructor

Prabhakaran S

Principal Data Scientist

My name is Selva, and I am super excited to mentor you on this course!

I head the Data Science team for a global Fortune 500 company and over the last 10 years of my data science experience I've deployed 20+ global products. I'm also the Founder and Chief Author of Machine Learning Plus, which has over 4M annual readers.

I specialize in covering the in-depth intuition and maths of any concept or algorithm. And based on my existing student requests, I've put up the series of courses and projects with detailed explanations, just like on-the-job experience. Hope you love it!

from 3,965 ratings

4.92

learners

57K+

courses

85