PEDIGREE MATTERS

Learn Machine Learning from India’s best Institute

Great Lakes Certificate

Rated 4.6/5

by 95% Participants

3 Million +

LEARNING HOURS DELIVERED

  • Ranked #1 in Analytics Education*

    Great Lakes' program has been ranked as the #1 in India for 3 years in a row!

  • 66% SUCCESS

    66% of our alumni have transitioned to roles in analytics , data science and machine learning.

  • WEEKEND MENTORSHIP

    MLCP is a mentorship-driven online program. Participants attend weekend mentorship sessions with Machine Learning experts and Data scientists.

  • CAREER SUPPORT

    Get access to Great Learning Machine Learning & Data Science Job board with regular postings from leading companies.

How Does Mentorship Work?

01Personalised mentorship: The most effective way to learning online

Participants learn in small groups of 5 & every group is assigned a Machine Learning mentor. Every participant gets access to personalised mentorship by engaging through weekend online sessions with one of our 100+ distinguished Machine Learning and Data Science mentors.

02The best of industry and academia

Participants learn from digital content created by some of India’s top rated Machine Learning faculty. On weekends, participants are led by their mentors as they work on data sets, projects and problem walk-throughs in Machine Learning & Data Science.

03Career coaching helps you connect the dots

Mentors inspire and guide participants at each step of their learning. Our mentors go beyond concept walkthroughs, doubt clearing and projects to help participants achieve their learning goals and also support them in their career transition in Machine Learning & Data Science.

The Great Learning Experience

MLCP is a one-of-its-kind innovative online program that provides a structured learning framework to participants for effective learning and application of Machine Learning & Data Science concepts.

Personalized Learning

You learn from industry experts not only through content but also through mentor-driven personalized learning sessions. Each module has recorded content that is followed by a session with an industry mentor who helps students master Machine Learning & Data Science tools and techniques and clears any doubts in a small group of 5 participants.

Experiential Learning Projects

An experiential learning project at the end of every module helps candidates internalize their understanding of the content consumed. Our coursework and practical assignments are designed to enable candidates to apply what they have learned during self-study and industry sessions.

Industry Exposure

Each week, participants get access to industry videos and webinars other than personalized learning sessions. Delivered by industry leaders, these resources are business-relevant, provide insights on current industry knowledge and solving real-life business problems.

Great Lakes Advantage

World-class award-winning faculty from Great Lakes ensure that the candidates learn through an exhaustive curriculum with hands-on experience. All participants upon successful competion are awarded a certificate by Great Lakes.

Distinguished Mentors

Candidates learn from 100+ distinguished Machine Learning experts who mentor them throughout the course of the program. Our Machine Learning mentors are thought-leaders in different domains with several years of industry experience and impart practical knowledge and industry insights in participants’ learning jouney.

Career Enhancement Sessions

The Program includes career development sessions which help participants identify their strengths, a customised career path and empowers them to clear interviews. Interacting with industry practitioners also helps participants gain exposure and experience in transitioning their careers.

Program Structure

  • weekend Instructor Led Classes

    48 hours of personalised mentorship from Machine Learning & Data Science professionals working in leading companies.

  • Online Content

    Best-in-class recorded content from expert faculty and industry mentors.

  • 7 Hands-On Projects

    Practical assignments, case studies and instructor-led practice sessions on data sets.

Foundations

STATISTICAL LEARNING
  • Statistical analysis concepts
  • Descriptive statistics
  • Introduction to probability and Bayes theorem
  • Probability distributions
  • Hypothesis testing & scores
  • Experiential learning project
Python for Machine Learning
  • Python Overview
  • Pandas for Pre-Processing and Exploratory Data Analysis
  • Numpy for Statistical Analysis
  • Seaborn for Data Visualization
  • Case Studies and careers
  • Experiential Learning project

MACHINE LEARNING MODULE

SUPERVISED LEARNING
  • Introduction to Machine Learning
  • Supervised Learning concepts
  • Linear Regression
  • Logistic Regression
  • K-NN Classification
  • Naive Bayesian classifiers
  • SVM - Support Vector Machines
  • Experiential Learning project
UNSUPERVISED LEARNING
  • Unsupervised Learning concepts
  • Clustering approaches
  • K Means clustering
  • Hierarchical clustering
ENSEMBLE TECHNIQUES
  • Decision Trees
  • Introduction to Ensemble Learning
  • Different Ensemble Learning Techniques
  • Bagging
  • Boosting
  • Random Forests
  • Stacking
  • Experiential Learning project
  • PCA (Principal Component Analysis) and Its Applications
FEATURIZATION, MODEL SELECTION & TUNING
  • Text Analytics
  • Feature extraction
  • Model Defects & Evaluation Metrics
  • Model selection and tuning
  • Comparison of Machine Learning models
  • Experiential Learning project
RECOMMENDATION SYSTEMS
  • Introduction to Recommendation Systems
  • Types of Recommendation Techniques
  • Collaborative Filtering
  • Content based Filtering
  • Hybrid RS
  • Case Study
  • Performance measurement
  • Experiential Learning project

Experiential Projects

Here are some of the projects that participants would be doing in the Machine Learning Certificate Program.

Building a machine learning model to gather sentiment Score from reviews on Amazon

This project involves building a machine learning model that can predict the sentiment score from the text available in Reviews dataset from Amazon website. Extract suitable features from the unstructured text and apply the machine learning model to get the sentiment score to understand people’s sentiments, attitudes or emotions towards certain Amazon products.

Techniques:

Feature Selection or Extraction, Sentiment Analysis, Text Analytics

Artist discovery and Personalised music recommendation using Last.fm data set

Using Last.fm music dataset, participants learn to apply user based collaborative filtering and other Recommendation algorithms to identify less-known Artist and new artists, enabling user to explore new songs music based on their taste. Also, participants get to build a prediction model to predict whether a user will listen to an artist’s songs and frequency of listening for a particular song.

Techniques:

Exploration Data Analytics, Recommendation algorithms, User profiling, Prediction

Dimensionality Reduction through Principal Component Analysis

This project involves step by step approach to implement Principal Component Analysis (PCA) using Python. A wine dataset with 13 attributes are used to achieve a new feature-set with lower number of dimensions that can be used for further analysis.

Techniques:

Unsupervised Learning, Principal component analysis, dimension reduction techniques

Creating a model to identify prospective customers for loans

The project involves identification of potential customers for the personal loan product of a bank. Ensemble modeling techniques are leveraged to predict the propensity of a prospect to purchase the loan. This enables the bank to devise targeted marketing campaigns to increase the conversion rate with minimal budget.

Techniques:

Supervised Learning, Ensemble Techniques, Model Selection

Sentiment Analysis on Twitter

This project enables participants apply sentiment analysis to understand user opinions and identify trends on different topics using data from Twitter.

Techniques:

Sentiment Analysis

Tools and Techniques

Python (Pandas, Numpy, Scipy, Matplotlib, Seaborn, Scikit-Learn)

 

Learn from THE BEST MACHINE LEARNING & DATA SCIENCE FACULTY

The faculty pool of the program consists of leading academicians in the field of Machine Learning & Data Science along with several experienced industry practitioners from leading organizations.

Mukesh Rao

Faculty, Machine Learning

Mr. Gurumoorthy P

Faculty, Data Science And Machine Learning

Here's what some of our past students have to say

One of my friends referred me to this program and so-far my experience in the program is really good. The program has good content and has a relevance with real-life scenarios. The best part is I am able to enjoy the learning part despite such a busy work schedule.

Pijush Maity

Pijush Maity

IBM

The overall experience has been great. The highlight is the assistance provided by the program support and the knowledge sharing that happens in the group. The way the doubts are being cleared is one of the good part of this program. The content is also very good.

Srikar Makala

Srikar Makala

HSBC

The mentorship sessions effectively aroused interest and passion of participants. Industry-relevant examples were well used throughout. The mentorship sessions were invaluable in helping us apply Machine Learning.

tesimonial image

Maheshwaran Sridharan

IT Manager

Admission Details Machine Learning Certificate Program

Following are the eligibility criteria and selection process for the program.

ELIGIBILITY
  • Applicants should have a bachelor's degree with a minimum of 50% aggregate marks or equivalent.

  • Preference will be given to candidates with Engineering, Mathematics, Statistics, and Economics background.

SELECTION PROCESS
  • Interested candidates need to apply by filling up an Online Application Form.

  • The Admissions committee and faculty panel will review all the applications and shortlist candidates based on their profiles.

  • Offer will be made to selected applicants

*Admissions will be closed once the requisite number of candidates have been admitted into the program.

PAYMENT Details
for the - Machine Learning Certificate Program

Following are the payment details for the program:

FEES

1,25,000 + GST

INCLUDES

Online Content

Tuition Fee

Learning Material

Mentorship Sessions

PAYMENTS

Candidates can pay the program fee through Cheque, DD, Net banking, Credit Cards or Debit Cards.*

FINANCIAL AID

Pay in 12 EMIs at 0% interest Rate with ZestMoney. Start learning at Rs. 9833/month!

 

Mark the Dates

Here are the Application Deadlines for the program

Upcoming Application Deadline: 18th October 2018

We follow a rolling admission process and admissions are closed once the requisite number of participants enroll for the upcoming batch. So we encourage you to apply early and secure your seat. Apply Now

Batch starts on: 24th November, 2018
Download Brochure!