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  • Machine Learning Basic
    to Advance with python

    Learn to build real-world Machine Learning
    applications using python

    Register now

About the Course

Machine learning with Python course covers the basics to advanced topics gradually that will help a beginner to walk from no or minimal knowledge of machine learning in Python to become a master practitioner. This training course consists of three parts. The first part covers the basics of python, the second part covers practical implementation with different Python packages and the third part covers the fundamentals of Machine Learning.

The course is designed and delivered by our Amrita TBI Fab Lab team. Amrita TBI Fab Lab acts as a springboard for the innovators by helping them nurture their ideas through its digital fabrication and prototyping facilities. Amrita TBI is a National Award Winner for being the best startup incubator in India.

 

 

Course Overview

Key Highlights

  • Designed for Beginners to
    Intermediate learners

  • 30+ hours of learning

  • Learn Machine Learning
    projects from Scratch

  • Hands-on Projects with
    real-world applications.

  • Assignments and personalized feedback
    to facilitate improvement

  • Instructional manuals
    and resources

  • Certificate from Amrita TBI,
    Amrita Vishwa Vidyapeetham

  • Best-in-Class content
    developed by experts

Machine Learning with Python- Basics to Advanced

Course Fee: Rs 3000/-

Date: 26 October 2021 - 9 November 2021
Time: 4:00pm - 6:00pm

Register Now

COURSE CONTENT

PART1

  • Python Identifiers.
  • Python Keywords.
  • How to write a program in Python?
  • How to write Code Blocks (Indentation & Suites) in python?
  • Basic Object Types.
  • Comments in Python.
  • Multiline Statement.
  • Basic Operators.
  • Control Structure.
  • Lists.
  • Tuple.
  • Sets.
  • Dictionary.
  • When to Use List vs. Tuples vs. Set vs. Dictionary?
  • How to create User-Defined Functions in Python?
  • What is meant by Module?
  • How to import modules in Python programs?
  • File Input/output operations.
  • How to handle an Exception in python?
  • What is meant by Machine Learning?
  • What are the different categories in Machine Learning?
  • What are different python packages for Machine Learning?
  • Which are the packages most widely using for data analysis?
  • How to work with the Python Package “Numpy “?
  • How to work with the Python Package “Pandas”?
  • How to plot a data analysis graph with the package “Matplotlib”?

 

  • How to deal with missing data in the data analysis?
  • How to normalize the data in the data analysis?
  • How to predict the flower with its petal and sepal length using Univariate analysis?
  • How to predict the flower with its petal and sepal length using Multivariate analysis?
  • How to predict the grade of a student’s using a correlation matrix in data analysis?
  • How to predict the price of a house by regression model? (Supervised Learning Regression)
  • How to predict, student’s pass /fail by classification model? (Supervised Learning Classification)
  • How to develop a Logistic Regression model?
  • How to develop a Support Vector Machine Algorithm?
  • How to work with the KNN algorithm?
  • How to predict seasonal sales in the market by the ARIMA algorithm?
  • Unsupervised Algorithm
  • How to classify different species of plants with k means clustering algorithm?

WHO THIS
COURSE IS FOR

Anyone interested to gain practical skills in Machine Learning

Research scholars who want to learn and complete their projects in ML

Students who are looking to learn a skill that makes them job-ready

Working professionals and freelancers who want to upskill their career

Entrepreneurs developing Machine Learning applications

Testimonials

The Instructor was more interactive and encouraged questions. Assignments and resources helped us to improve our skills.

Prathyusha Robbi

Student

This course has hands-on training with sufficient time, that helps everyone to understand and execute the codes on their own.

Sreedevi A. G

Student

The instructor handled all the sessions very effectively from basics to advanced.

Anu Vijay

Researcher

The course was easy to follow even for a beginner. The instructor was patient and open to feedback. Learned many techniques which could help me speed up my official tasks.

Barath

Working Professional