Machine Learning In-Depth (With Python)

Machine Learning In-Depth (With Python), available at $59.99, has an average rating of 4.75, with 24 lectures, based on 4 reviews, and has 178 subscribers.

You will learn about Machine Learning In-depth, Covers Supervised Learning (Regression and Classification) Covers Unsupervised Learning (Dimensionality Reduction and Clustering) This is pre requisite for Deep Learning, Reinforcement Learning, NLP, and other AI courses Completing this course will also make you ready for most interview questions for Machine Learning This course is ideal for individuals who are People looking to advance their career in Data Science and Data Analytics or Already working in Data Science/ Data Analyst Roles and want to clear the concepts or Want to make base strong before moving to Machine Learning, Deep Learning, Reinforcement Learning, NLP, and other AI courses or Currently working as Data Analyst and want to progress to Data Science Roles It is particularly useful for People looking to advance their career in Data Science and Data Analytics or Already working in Data Science/ Data Analyst Roles and want to clear the concepts or Want to make base strong before moving to Machine Learning, Deep Learning, Reinforcement Learning, NLP, and other AI courses or Currently working as Data Analyst and want to progress to Data Science Roles.

Enroll now: Machine Learning In-Depth (With Python)

Summary

Title: Machine Learning In-Depth (With Python)

Price: $59.99

Average Rating: 4.75

Number of Lectures: 24

Number of Published Lectures: 24

Number of Curriculum Items: 24

Number of Published Curriculum Objects: 24

Original Price: $199.99

Quality Status: approved

Status: Live

What You Will Learn

Machine Learning In-depth,
Covers Supervised Learning (Regression and Classification)
Covers Unsupervised Learning (Dimensionality Reduction and Clustering)
This is pre requisite for Deep Learning, Reinforcement Learning, NLP, and other AI courses
Completing this course will also make you ready for most interview questions for Machine Learning

Who Should Attend

People looking to advance their career in Data Science and Data Analytics
Already working in Data Science/ Data Analyst Roles and want to clear the concepts
Want to make base strong before moving to Machine Learning, Deep Learning, Reinforcement Learning, NLP, and other AI courses
Currently working as Data Analyst and want to progress to Data Science Roles

Target Audiences

People looking to advance their career in Data Science and Data Analytics
Already working in Data Science/ Data Analyst Roles and want to clear the concepts
Want to make base strong before moving to Machine Learning, Deep Learning, Reinforcement Learning, NLP, and other AI courses
Currently working as Data Analyst and want to progress to Data Science Roles

Machine Learning In-Depth (With Python)

1. What will students learn in your course?

Machine Learning In-depth, Covers Introduction, Supervised Learning including regression and classification, Unsupervised Learning including dimensionality reduction and clustering.

Very few courses covers basics and algorithm in detail, and here you will find clear and simple explanation and practical implementation

Completing this course will also make you ready for most interview questions for Data Science /Machine Learning Role related to Supervised Learning including regression and classification, Unsupervised Learning including dimensionality reduction and clustering.

This is Pre-requisite for Deep Learning, Reinforcement Learning, NLP, and other AI courses

2. What are the requirements or prerequisites for taking your course?

Good to do my “Data Analysis In-Depth (With Python)” course on Udemy

3. Who is this course for?

People looking to advance their career in Data Science and Machine Learning roles

Already working in Data Science/ ML Ops Engineering roles and want to clear the concepts

Want to make base strong before moving to Deep Learning, Reinforcement Learning, NLP, LLM, Generative AI and other AI courses

Currently working as Full Stack developer and want to transition to Machine Learning Engineer roles

4. Is this course in depth and will make industry ready?

Absolutely yes, it will make you ready to creack Machine Learning Interviews and solve ML problems. This will also lay strong foundation for Deep Learning, Reinforcement Learning, etc

5. I am new to IT/Data Science, Will i understand?

Absolutely yes, it is taught in most simplest way for every one to understand

Course Curriculum

Chapter 1: Machine Learning In-Depth Course

Lecture 1: Introduction to Data Science Career Path

Lecture 2: Day 1 – Introduction to ML

Lecture 3: Day 2A – ML End to End (Day 1 of 2)

Lecture 4: Day 2B – ML End to End (Day 1 of 2)

Lecture 5: Day 3 – ML End to End (Day 2 od 2)

Lecture 6: Day 4 – ML – Linear Regression

Lecture 7: Day 5 – ML – Linear Regression Continue

Lecture 8: Day 6 – ML – Linear Regression Continue

Lecture 9: Day 7 – ML – Linear Regression Continue

Lecture 10: Day 8 – ML – Linear Regression Practical

Lecture 11: Day 9 – ML – Introduction to Classification

Lecture 12: Day 10 – ML – Introduction to Classification

Lecture 13: Day 11 – ML – Introduction of Logistics Regression

Lecture 14: Day 12 – ML – Logistics Regression Practical

Lecture 15: Day 13 – ML – Introduction of Decision Tree

Lecture 16: Day 14 – ML – Decision Tree (Cont) and Hands On

Lecture 17: Day 15A – ML – Random Forest and Hands on

Lecture 18: Day 15B – ML – Random Forest and Hands on

Lecture 19: Day 16 – ML – Support Vector Machines

Lecture 20: Day 17 – ML – Support Vector Machines Hands On

Lecture 21: Day 18 – ML – Principal Component Analysis

Lecture 22: Day 19 – ML – Principal Component Analysis Hands On

Lecture 23: Day 20 – ML – Clustering

Lecture 24: Day 21 – ML – Clustering Hands On

Instructors

Harish Masand
Data Engineering and Data Science(Big Data, ML, AI )

Rating Distribution

1 stars: 0 votes
2 stars: 0 votes
3 stars: 0 votes
4 stars: 2 votes
5 stars: 2 votes

Frequently Asked Questions

How long do I have access to the course materials?

You can view and review the lecture materials indefinitely, like an on-demand channel.

Can I take my courses with me wherever I go?

Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!

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