Machine Learning Training

(3) 3 Ratings

Course Schedule

30

JUL

Mon - Sat

07:30 PM - 10:00 PM ( IST )

06

AUG

Mon - Fri

11:00 AM - 02:00 PM ( IST )

11

AUG

Sat - Sun

05:30 AM - 06:30 AM ( IST )


Total Learners

1250 Learners


LMS Access

365 days

Course duration

30 days


Support

24/7 support

Can't find convenient schedule?

Our experts can help you find a batch that meets your needs

The Instructor for this course is from one of the Big5 Companies in the world.

Drop us a Query

I agree to the Training T&C

Modes of Training

Corporate Training

Live, Classroom Or Self Paced Training

Online Classroom

Attend our Instructor Led Online Virtual Classroom

Self Paced Training

Comprehensive Recorded Videos by Experts to learn at your own pace

Course Features

Live Instructor-led Classes

This isn't canned learning. Its dynamic, its interactive, its effective

Expert Educators

Only the best or they're out. We are constantly evaluating our trainers

24&7 Support

We never sleep. Need something answered at 3 am? No Problem

Flexible Schedule

You don't learn as per our calendar. We work according to yours

☰ Details

Course Curriculum

Introduction to Machine Learning

  • Introduction
  • Regression Algorithms
  • Classifiers: Bayesian and kNN
  • Tree Based Algorithms 
  • SVM and Improving Performance. 

Data Science with R

  • An Overview of Analytics and Data Science
  • Business Statistics and Application
  • An Introduction to R
  • Predictive Models and Machine Learning. 

Introduction to Python

  • Installation of Python framework and packages: Anaconda & pip
  • Writing/Running python programs using Spyder Command Prompt
  • Working with Jupyter notebooks
  • Creating Python variables
  • Numeric , string and logical operations
  • Data containers : Lists , Dictionaries, Tuples & sets
  • Practice assignment.

Iterative Operations & Functions in Python

  • Writing for loops in Python
  • While loops and conditional blocks
  • List/Dictionary comprehensions with loops
  • Writing your own functions in Python
  • Writing your own classes and functions
  • Practice assignment.

General Boosting & Bagging

  • Decision Tree Ensembles
  • Bagging and Boosting
  • Case Study: Analysis of Credit Data
  • Case Study: The Titanic Accident
  • Case Study: Comparing Algorithms. 

Support Vector Machines

  • Introduction to idea of Observation based Learning
  • Distances and similarities
  • K Nearest Neighbours (KNN) for Classification 
  • Brief Mathematical background on SVM 
  • Regression with KNN & SVM, Case Study. 

Data Handling in Python using NumPy & Pandas

  • Introduction to NumPy arrays, functions & properties
  • Introduction to Pandas & data frames
  • Importing and exporting external data in Python
  • Feature engineering using Python.

Generalised Linear Models in Python

  • Linear Regression
  • Regularisation of Generalised Linear Models
  • Ridge and Lasso Regression
  • Logistic Regression
  • Methods of threshold determination and performance measures for classification score models
  • Case Study.

Machine Learning Basics

  • Converting business problems to data problems
  • Understanding supervised and unsupervised learning with examples
  • Understanding biases associated with any machine learning algorithm
  • Ways of reducing bias and increasing generalisation capabilites
  • Drivers of machine learning algorithms
  • Cost functions
  • Brief introduction to gradient descent
  • Importance of model validation
  • Methods of model validation
  • Cross validation & average error.


Course Description

What are the Course Objectives of Machine Learning?

  • Understand the working of Predictive Models and Business Analytics & Statistics.
  • Learn about the Regression Algorithms and Improved Performance.
  • Hands-on sessions in ‘R’.
  • Explanation about Neural Networks.

Who Should Attend this Training?

  • Data Analysts
  • End Users
  • Programmers
  • Any graduate interested in the specific field.

What are the Pre-requisites for this Course?

  • There are no pre-requisites involved in learning Machine Learning. This course is specifically designed for the end user whose interest lies in the field.

FAQ

Do you have self paced training?

Yes, we offer self paced training

How do you provide training?

We offer three different modes of training. Instructor Led Live Training, Self Paced Training and Corporate Training

Do you offer any discounts?

Yes we offer discounts for group of 3 plus people.

Can I choose timings that suits my schedule?

Yes we are the only company where we work with students and offer flexible timings which fits your schedule

Who are the Instructors?

All our instructors are from MNC companies who have real time experience of more than 10 years.

Can I attend a demo session before joining?

Yes we offer a free demo session with the instructors. The trainer will answer all your queries and share the course agenda.

Course Reviews

Anusha

I have enrolled in Machine Learning from LTB. The content of the course is elaborate and easy to understand. The faculty has clarity in his way of explaining, maintains a very good balance between theory and the practical process. It has been a great learning experience for me.

Harika

The course was very informative. The study material provided by the trainer was extremely helpful and very easy to understand. Thank you LTB.

Sukesh

I came across Live Trainings Bangalore while I was searching for Fast Track courses for Machine Learning. Their coordinators and instructors responded positively and I was able to get a good conceptual overview. Thank you LTB.