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Machine Learning with Python USD

Week 1

Python Introduction

Week 2

Jupyter Overview

Week 3

Python for Data Analysis - NumPy

Week 4

Python for Data Analysis - Pandas

Week 5

Python for Data Visualization - Matplotlib

Week 6

Introduction to Machine Learning

Week 7

Linear Regression

Week 8

Logistic Regression

Week 9

K Nearest Neighbors

Week 10

Principal Component Analysis

Week 11

Recommender Systems

Week 12

Natural Language Processing

Week 13

Big Data and Spark with Python

Week 14

Neural Nets and Deep Learning

Week 15

Deep Learning With Tensorflow

Machine Learning with Python USD

₹899/-
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About this course

Smart algorithms are being used everywhere to make lives of humans easier. Smart watches, smart homes and smart cities are being created with the help of Artificial Intelligence and Machine Learning is a field that plays a major role in these innovations. It uses statistical methods to help systems learn data without being programmed.

Machine Learning is one of the most desired skills employers are looking for in the recent times and there are over 50,000 Machine Learning jobs available in the market currently. Gain an insight and develop a hands-on-experience in using Python for machine learning with this instructor-led online classes held by industry experts. This course provides learners from all academic and professional backgrounds a project-based practical learning experience.

Expedite your career by attaining Machine Learning skills – Become an ML Expert in 7 Weeks.A comprehensive course that has the right blend of  conceptual and hands-on workshops to carve an ML Expert out of you.

Course Schedule

Course Start Dates

TBA.

Free Webinars

TBA.

FAQs

Who should enroll to course

This course is meant for people looking to learn Machine Learning. We will start out to understand the pre-requisites, and then go on to solve case studies using Data Science concepts.

When will the classes be held in this course?

There are 2 ways Self Paced and Online classes. Online classes would be held Saturday and Sundays. .

How many weeks should i practice to complete the course?

If you can put between 6 to 8 hours a week, you should be able to finish the course in 6 to 8 weeks..

What is the refund policy?

The fee for this course is non-refundable..

Syllabus

Week 1

Python Introduction

Week 2

Jupyter Overview

Week 3

Python for Data Analysis - NumPy

Week 4

Python for Data Analysis - Pandas

Week 5

Python for Data Visualization - Matplotlib

Week 6

Introduction to Machine Learning

Week 7

Linear Regression

Week 8

Logistic Regression

Week 9

K Nearest Neighbors

Week 10

Principal Component Analysis

Week 11

Recommender Systems

Week 12

Natural Language Processing

Week 13

Big Data and Spark with Python

Week 14

Neural Nets and Deep Learning

Week 15

Deep Learning With Tensorflow

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