Machine Learning Course in Bangalore With Placements | iMADE

INTERNATIONAL MANAGEMENT
ACADEMY FOR DIGITAL ECONOMY

(Approved by Govt. of India; Govt. of Karnataka; ISO 9000:2015)

Machine Learning

Machine Learning

MACHINE LEARNING is a different approach of getting computers to act without being explicitly programmed. Machine Learning algorithms are at the core and important piece of data science.  Machine Learning is seen as the “future technology of business”. It is expected to go far beyond the highest level of accuracy and understanding. With its dramatic improvements in past few years, Machine Learning  has taken over a main stream business as increasing number of organizations are employing ML to achieve real business results. Now, it is so pervasive that we might be using it dozens of time in our daily life without knowing it.

PROGRAM HIGHLIGHTS

Machine learning has evolved as a great career track by itself. A quick job search in Google will reveal hundreds of thousands of job opportunities around the globe. This course lays a solid foundation for ML aspirants with high level theory and concept along with hands on coding of popular Machine Learning algorithms : Linear and Logistic Regression, K-means clustering, SVM (Support Vector Machines), KNN (K -Nearest Neighbours) and Neural Networks. The syllabus is aligned with international market trends. Participants gain a right perspective through:

  • Machine Learning with holistic approach
  • High level theory of popular Machine Learning Algorithms
  • Hands on coding of popular ML algorithms on classic data sets

Learning from the Program

In this course, you will learn about the most effective machine learning techniques, and gain practice implementing them and getting. More importantly, you’ll learn about not only the theoretical underpinnings of learning, but also gain the practical know-how needed to quickly and powerfully apply these techniques to new problems.

This course provides a broad introduction to machine learning, datamining, and statistical pattern recognition. Topics include:

  1. Supervised learning (parametric/non-parametric algorithms, support vector machines, kernels, neural networks).
  2. Unsupervised learning (clustering, dimensionality reduction, recommender systems, deep learning).
  3. Best practices in machine learning (bias/variance theory; innovation process in machine learning and AI).

The course will also draw from numerous case studies and applications, so that you’ll also learn how to apply learning algorithms to building smart robots (perception, control), text understanding (web search, anti-spam), computer vision, medical informatics, audio, database mining, and other areas.

WHAT MORE YOU WILL LEARN

Machine Learning Course at the Digital Academy will allow participants to dive deep into the Machine Learning concepts in an organized way. Designed as a holistic course covering both the intensive training sessions plus hands-on labs for the following skill sets

  • Python for Machine Learning
  • Machine Learning Associate
  • Machine Learning expert
  • Time series foundation
  • Model deployment (Flask-API)
  • Deep Learning -CNN Foundation

Who Should Take This Program

  • Fresh Engineers graduates aspiring for career in Machine Learning  or Data Science
  • Professionals planning to shift career in Machine Learn or Data Science in general
  • Senior professionals, who want to gain solid foundation on Machine Learning to manager Data Science projects
  • Candidates pursuing Data Scientist tracks
  • Working Software and IT Professionals, Data Professionals

COURSE CURRICULUM

INTRODUCTION

  • What is Machine Learning
  • Supervised Learning
  • Unsupervised Learning
  • 1 practice exercise

LINEAR REGRESSION WITH ONE VARIABLE

  • Model Representation
  • Cost Function – Intuition
  • Gradient Descent
  • Gradient Descent Intuition
  • Gradient Descent For Linear Regression
  • 1 practice exercise

LINEAR ALGEBRA REVIEW

  • Matrices and Vectors
  • Addition and Scalar Multiplication
  • Matrix Vector Multiplication
  • Matrix Multiplication
  • Matrix Multiplication Properties
  • Inverse and Transpose
  • 1 practice exercise

REGULARIZATION

  • The Problem of Overfitting
  • Cost Function
  • Regularized Linear Regression
  • Regularized Logistic Regression
  • 1 practice exercise

GNU OCTAVE 2020 / MATLAB TUTORIAL

  • Basic Operations
  • Moving Data Around
  • Computing on Data
  • Plotting Data
  • Control Statements: for, while, if statement
  • Vectorization
  • 1 practice exercise

LOGISTIC REGRESSION

  • Classification
  • Hypothesis Representation
  • Decision Boundary
  • Cost Function
  • Simplified Cost  Function and Gradient Descent
  • Advanced Optimization
  • Multiclass Classification: One-vs-all
  • 1 practice exercise

LINEAR REGRESSION WITH MULTIPLE VARIABLES

  • Multiple Features
  • Gradient Descent for Multiple Variables
  • Gradient Descent in Practice I – Feature Scaling
  • Gradient Descent in Practice II – Learning Rate Features and Polynomial Regression
  • Normal Equation1
  • Normal Equation Non-invertibility
  • Working on and Submitting Programming Assignments
  • 1 practice exercise

NEURAL NETWORKS: REPRESENTATION

  • Randomly initialize weights
  • Implement forward propagation to get the hypothesis
  • Compute the cost function to get the errors
  • Implement back propagation to compute partial derivatives (optimizing the parameters through errors)

  • Apply gradient checking (comparing backpropagation with numerical estimate)
  • Disable gradient checking
  • Use an optimization method to minimize the cost function with it’s corresponding parameters

BOOT CAMP

  • Industry Master Class – Artificial Intelligence
  • AI – Machine Learning with R

Delivery

  • The courses are offered in blended mode i.e. Classroom learning is supported by online activity.

What makes Machine Learning course at MADE ACADEMY important?

  • Project Mentoring by industry professionals.
  • Live projects by global AI and ML solution providers
  • Participants gain hands-on learning by working on live projects
  • Designed by and for Working Professionals
  • Case Studies and Assignments
  • Practicum for Hands on Training
  • Capstone Projects
  • Industry Mentorship Sessions
  • 24×7 support
  • Placement Guaranteed with Top Players
  • Post Completion Support
  • Revision Sessions: Participants will get full opportunities for revisions and to clarify any doubts with our chief Data Scientist even after completion of the course

Team Members

mksharma

PROF MANOJ KUMAR SHARMA

MBA, M.Tech, M.Sc (Comp. Sc.)

Specialization Area: Product Development | Training & Mentoring | Brand Management | Corporate Communication | Digital Marketing | Education Marketing & Counseling Services | Channel Management | Event Management | Media Planning & Promotions | Data Management

sparshsarswat

SPARSH SARSWAT

PGDBM (Marketing), MCA, BCA

Specialization Area: Brand Promotion | Business Development | Training | Product Development | Digital Marketing | Counselling | Pipeline Management | Corporate Relations | Education Marketing | Event Management | Media Buying & Planning| Digital Sales

Prospective Placement Providers

FOLLOW UP AND CAREER SUPPORT PROGRAMME:

Completion of our well-structured courses on Machine Learning enables the aspirants to explore newer heights in career advancement in Machine Learning.  The career prospects for Machine Learning are on the rising curve.  MADE ACADEMY is India’s top-ranked Digital Economy training provider, accredited by NSDC, Dept of ITBT Govt of Karnataka, Dept of Electronics Govt of India, delivering different training courses on Digital Technologies including Machine Learning.

MADE will provide following support services for our participants

  • 100% Guaranteed Placement: We will ensure your placement in MNC’s, Mid & Small Size Companies or Ecommerce portals
  • Resume Support: Resume makes the first impression. At MADE ACADEMY you can curate a customized resume with the support of experts to make your first impression the best one
  • Interview Questions: Team of experts shall equip you with a set of probable interview questions and answers to face the interviews confidently
  • Mock Interviews: As part of Action Learning our experts will help you to increase your placement success by practicing numerous mock interview sessions
  • Job Updates: MADE career planning team shall post all latest job updates
  • Help in setting up your own business

 Eligibility Criteria

Academic qualification
  • Preferred Engineering Graduates
  • Other Graduate Degree with Mathematics or Statistics
  • Sufficient knowledge of computer operation particularly web application
  • Basic knowledge of programming and application of statistical data for decision making will be useful
Application Process

Fill up the Application Form through
the link provided for Online Application
Apply Now

CERTIFICATION

Earn a Certificate of Post Graduate Diploma in Machine Learning from the MANAGEMENT ACADEMY FOR
DIGITAL ECONOMY IN INDIA endorsed by the industry and Govt agency.