Advanced Data Science Program

One to One with Faculty : Python + Data Science + Machine Learning + Deep Learning
Self Paced : R Programming + Tableau + MySql + Adv Excel + Java
Live Technical Chat Support
Mentorship
Lifetime Content Access
Assessment & Mock Interview
Assessment + Projects
Placement Guidance
Student Project Samples

Advanced Data Science Program
Why Choose Us

Personalised One on One Training

Learn One on One with Trainers from Industry with 20 Plus years of Experience in Consulting & Academics.

Mentorship

During your course you will be interacting with experts from the industry which will enhance your skills and thinking significantly thus benefiting in your journey to a successful career.

Profile Build with Projects

Showcase your Capstone projects as part of your Profile Building Collateral

Placement Assistance

Our team will also assist you in placements by providing Network access for the positions in Analytics space.

Industry Endorsement

This course has been endorsed by SiCureMi an IIT Delhi incubated Analytics Firm.

Learning Management System

Access Content on LMS, Manage Projects Submission, Tech Support Logging and Digital Certificate

Industry Membership

Get the Optional Chartered Data Scientist Designation from Association of Data Scientist.

Program Outline

Introduction to Data Science

  • Module 1: Introduction To Data Science

  • Module 2: Life cycle of data science

  • Module 3: Skills required for data science Career path in data science

  • Module 4: Applications of data science

  • Module 5: Technology

Live

Discussion & Guidance

Statistics in Data Science

  • Module 6: Introduction to Data

  • Module 7: Measures of Central Tendency

  • Module 8: Measures of Dispersion

  • Module 9: Measures of Skewness and Kurtosis

  • Module 10: Inferential Statistics

  • Module 11: Random Sampling & probability Distribution

Online Project Submission

MCQ Assessment

Live

Discussion & Guidance

R for Data Science

  • Module 12: Installation & Environment Setup

  • Module 13: Data Types & Data Structures

  • Module 14: Data Import and Export

  • Module 15: Control Structures & Loops

  • Module 16: Functions in R

  • Module 17: R for Data Visualization

Online Project Submission

MCQ Assessment

Live

Discussion & Guidance

Python for Data Science

  • Module 18: Installation & Environment Setup

  • Module 19: Data Types

  • Module 20: Data Structures

  • Module 21: Operators

  • Module 22: Control Statements

  • Module 23: Loops

  • Module 24: Functions - Built In & User Defined

  • Module 25: Array Processing Package

  • Module 26: Data Manipulation Package

  • Module 27: Visualisation Package

Online Project Submission

MCQ Assessment

Live

Discussion & Guidance

Statistical Learning

  • Module 28: Statistical /Machine Learning

  • Module 29: Linear Regression (Real Estate Price Prediction Case Study)

  • Module 30: Logistic Regression (Direct Marketing Campaign Case Study)

  • Online Project Submission

    MCQ Assessment

    Live

    Discussion & Guidance

Unsupervised Machine Learning

  • Module 31: Association Rule Mining (Retail Recommendation Case Study)

  • Module 32: K Means (Market Segmentation Case Study)

  • Module 33: Time Series (Automotive Sales Forecasting Case Study)

  • Online Project Submission

    MCQ Assessment

    Live

    Discussion & Guidance

Supervised Machine Learning

  • Module 34: K Nearest Neighbours (Cancer Detection Case Study)

  • Module 35: Decision Tree (Diabetics Detection Case Study)

  • Module 36: Support Vector Machines (Hand Written Text Recognition Case Study)

  • Module 37: Ensemble Learning : Bagging, Random Forests, Boosting (Hr Attrition Prediction Case Study)

  • Online Project Submission

    MCQ Assessment

    Live

    Discussion & Guidance

Neural Networks & Deep Learning

  • Module 38: Artificial Neural Network (Functional Arithmetic Learner Case Study)

  • Module 39: Deep Neural Network (Sales Forecasting Case Study)

  • Module 40: Recurrent Neural Networks (Stock Price Prediction Case Study)

  • Module 41: Convolutional Neural Networks (Face Recognition Case Study)

  • Module 42: Computer Vision (Face Detection Case Study)

  • Online Project Submission

    MCQ Assessment

    Live

    Discussion & Guidance

Self Paced Modules

  • Stream 1: MySQL

  • Stream 2: Basic to Advanced Excel

  • Stream 3: Tableau

  • Stream 4: Java Programming

  • Stream 5: Business Analytics

  • Stream 6: Visual Analytics

Who should enroll for the Program ?

  • Those with Engineering or Programming background wanting to become a Data Scientist

  • Any Data Analyst or Software Developer aspiring to be a Data Scientist

  • Professionals wanting to build machine learning models, using distributed storage and distributed processing

  • Managers from Analytic background and those who are leading a team of Analysts

  • Those who have taken up data science course but don't feel confident about executing their learnings in real world scenarios

  • Above All any one who has curiosity of a child to Learn new things

  • Program Executed By

    Program will be executed by Mohan Rai, IIM qualified Trainer/Mentor/Consultant. Mohan Rai is an IIM Bangalore Alumni with more than 20 years experience in Analytics and has worked closely with different business heads in diverse domains.

    Corporate Trainings Executed

    What Clients Say

    Have a questions?

    Call Us

    Mobile: 8291450197
    Corporate Address:
    A 314, Sarita Building, Prabhat Industrial
    Complex, Next To Dahisar Check Naka,
    Western Express Highway, Dahisar East,
    Mumbai - 400068