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Learn Data Science, Machine Learning, Neural Networks with India's #1 course and upgrade your career skills with Bygrad

In collaboration with IBM

5,000+

Learners

Bygrad JobAssist™

Top Hiring Companies

06 Month

Recommnded 18-23 hrs/week

28ᵗʰ Aug 2021

Next Batch starts on

300+

Hiring Partners

Data Science Master Program

About the Program

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Academics

The Data Science Master Program is a post-graduation program that includes advanced coursework in artificial intelligence, machine learning, neural network, and high-performance computing. A well-known track specifically for studies in data science (the DSMP with IBM) is available.

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Careers

Join the ranks of technology industry visionaries who have degrees from IBM, Data Science is part of the largest alumni network in the country, with 215,000+ alumni worldwide. Wherever you are in the world, you’re never far from fellow ibm.

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Personalised Mentorship

Personalised 1:1 chat with mentors.  ask all your questions to whomsoever mentor you want to connect. Get a dedicated student mentor with proactive support every step of the way.

Key Features

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232 Hrs Instructor Led Training

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Certification and Job JobAssist

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104 Hrs Self-paced Videos

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Flexible Schedule

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Lifetime Free Upgrade

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24 x 7 Live Support & Access

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253 Hrs Project work & Exercises

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Ideal for both Working and Fresh Graduates

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Live Internship

Syllabus

Best-in-class content by leading faculty and industry leaders in the form of videos, cases and projects

Programming Languages and Tools Covered

WILL I GET CERTIFIED?

Upon successful completion of this data science program, you’ll earn an IBM- endorsed certification that will significantly strengthen your resume.

  • EARN YOUR CERTIFICATE

  • SHARE YOUR ACHIEVEMENT

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Instructors

Syllabus

Best-in-class content by leading faculty and industry leaders in the form of videos, cases and projects, assignments and live sessions

Machine Learning with Python


Introduction to Machine Learning

  • Introduction to Machine Learning

  • Python for Machine Learning

  • Supervised vs Unsupervised

Regression
  • Introduction to Regression

  • Simple Linear Regression

  • Model Evaluation in Regression Models

  • Evaluation Metrics in Regression Models

  • Multiple Linear Regression

  • Non-Linear Regression

Classification
  • Introduction to Classification

  • K-Nearest Neighbours

  • Evaluation Metrics in Classification

  • Introduction to Decision Trees

  • Building Decision Trees

  • Intro to Logistic Regression

  • Logistic regression vs Linear regression

  • Logistic Regression Training

  • Support Vector Machine

Clustering
  • Intro to Clustering

  • Intro to k-Means

  • More on k-Means

  • Intro to Hierarchical Clustering

  • More on Hierarchical Clustering

  • DBSCAN

Recommender Systems
  • Intro to Recommender Systems

  • Content-based Recommender Systems

  • Collaborative Filtering




Introduction to Data Science & Analytics Techniques


  • Introduction to Data Science
  • Introduction to Python
  • Data Analysis Pipeline
  • What is Data Extraction
  • Types of Data
  • Raw and Processed Data
  • Data Wrangling
  • Overview of the Analytics Techniques
  • Analytics
  • Business Intelligence
  • Business Analytics
  • Industry Examples




SQL for Data Science


Basic SQL

  • Introduction to SQL

  • DDL & DML Statement

  • SELECT Statement AGGREGATE functions

  • WHERE, ORDER BY, DISTINCT, GROUP BY, LIKE, AND & OR clause

  • UPDATE & DELETE query

Advanced SQL

  • JOINS

  • UNION, UNION ALL, INTERSECT

  • Using VIEWS & INDEXES

  • Sub Queries

  • NULL values & DATE function




Numpy


  • Indexing
  • ndarray
  • Array Creation
  • Data Type Objects
  • Data type Object (dtype) in NumPy
  • Basic Slicing and ALinear Algebra
  • Sorting, Searching and Counting
  • Set 1 (Introduction)dvanced Indexing
  • Iterating Over Array
  • Binary Operations
  • Mathematical Function
  • String Operations

  • Set 2 (Advanced)
  • Multiplication of two Matrices in Single line using Numpy in Python




Statistics & Probability


About Data

  • Data definition
  • Raw and Processed data
  • Data Types (NOIR)

Descriptive Stats

  • Measure of Central Tendency
  • Measure of Dispersion
  • Measure of Association

Probability

  • Basic terminology
  • Rules and Events
  • Conditional probability and Bayes theorem

Data Distribution

  • Skewness
  • t-Distribution
  • Uniform Distribution
  • Binomial Distribution
  • Poisson Distribution
  • Geometric Distribution
  • Gaussian Distribution
  • Standard Normal Distribution
  • Central Limit Theorem

Inferential Stats

  • Estimation technique
  • Hypothesis Testing (t-statistic calculations)

Sampling tecniques

  • Random Sampling,
  • Stratified Sampling

Statistical Tests

  • ANOVA
  • Chi-Square




Introduction to NLP


  • Syntactical Parsing
  • Text Preprocessing
  • Text to Features (Feature Engineering on text data)
  • Noise Removal
  • Lexicon Normalization
  • Lemmatization
  • Stemming
  • Object Standardization
  • Dependency Grammar
  • Part of Speech Tagging
  • Entity Parsing
  • Phrase Detection
  • Named Entity Recognition
  • Topic Modelling
  • N-Grams
  • Statistical features
  • TF – IDF
  • Frequency / Density Features
  • Readability Features
  • Word Embeddings
  • Important tasks of NLP
  • Text Classification
  • Text Matching
  • Levenshtein Distance
  • Phonetic Matching
  • Flexible String Matching
  • Important NLP libraries




Pandas


Pandas DataFrame

  • Creating a Pandas DataFrame
  • Dealing with Rows and Columns in Pandas DataFrame
  • Indexing and Selecting Data with Pandas
  • Boolean Indexing in Pandas
  • Conversion Functions in Pandas DataFrame
  • Iterating over rows and columns in Pandas DataFrame
  • Working with Missing Data in Pandas
  • Working With Text Data
  • Working with Dates and Times
  • Merging, Joining and Concatenating

Data Analysis

  • Data visualization using Bokeh
  • Exploratory Data Analysis in Python
  • Data visualization with different Charts in Python
  • Data Analysis and Visualization with Python
  • Math operations for Data analysis




Data Analysis & Wrangling


  • Data Analysis Pipeline
  • What is Data Extraction
  • Types of Data
  • Raw and Processed Data
  • Data Wrangling
  • Exploratory Data Analysis





Hours Content Available

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Live Learning

Sessions

Industry Projects

Programming Tools/ Languages

450+

20+

9+

183+

HOW DO YOU TRAIN?

Hands-on experiential learning is the core of our training methodology, because becoming a well-rounded professional takes much more than just rote learning. Our IBM curriculum places special emphasis on building analytical skills through hands-on practice.

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In-class Project

Go beyond traditional rote learning through the use of projects that simulate challenges faced by the industry.

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Case study

Real-world use cases and complex business scenarios that prepare you for the transition from academics to industry.

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Live Capstone Project

Work on a live business problem on completion of your course, guided by a dedicated Project Mentor.

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Virtual Labs

Learn on a state-of-the-art IBM virtual lab, with 24/7 access on tools such as Python and IBM Watson.

Industry Projects

Learn through real-life industry projects sponsored by top companies across industries

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Benefit by learning in-person with expert mentors

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Engage in collaborative projects with student-mentor interaction

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Personalised subjective feedback on your submissions to facilitate improvement

Automobile

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Car review blogs and tweets analysis

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E-commerce/Internet Business

Customer engagement and brand perception of Indian ecommerce - A social media approach

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IMDb Movie Analysis

Analyze movie data from the past hundred years and find out various insights...

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Healthcare

Prediction of user's mood using the smartphone data

Logistic Regression, Random Tree, ADA Boost, Random Forest, KSVM

WHAT CAREER SUPPORT WILL I GET?

Our Career Service team will offer you support, actionable tips and tricks as you learn AI with Bygrad to successfully bag that coveted machine learning job.

Revamping your resume to attract recruiter attention and leave a great first impression in any interview you attend.

INTERVIEW PREPARATION

Role-playing during mock interviews and Q&A rounds to mentally prepare you for success.

Why

BYGRAD

Your portfolio-worthy Capstone project and hackathon results are certain to give your profile that added boost and get recruiters to notice you.

PROFILE ENHANCEMENT

PLACEMENTS

We generate the Ability Score of every individual which is then sent to our more than 300+ recruitment partner organizations. At last, we organize campus placements every three months in Noida, Gurgaon, Ahmedabad, Bangalore, Mumbai and Chennai to place our students.

RESUME BUILDING

Our Learners Work At

Top companies from all around the world have recruited Bygrad alumni

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Career Transitions

Average Salary Hike

52%

600+

22L

Highest Salary

300+

Hiring Partners

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Bygrad Alumni

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Raj Kumar

>>

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Ritti Thakran

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>>

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Ankit Chaudhary

>>

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Vaidehi Vishnoi

>>

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Abhinandan Gupta

>>

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Anjali Bhatnager

>>

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Sushant Roy

>>

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Admission Process

There are 3 simple steps in the Admission Process which is detailed below

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Step 1: Fill in a Application Form

Step 2: Get Shortlisted & Receive a Call

Step 3: Block your Seat & Begin the Prep Course

Fill up the Application Form and one of our counselors will call you & understand your eligibility.

Our Admissions Committee will review your profile. Upon qualifying, an Email will be sent to you confirming your admission to the Program.

Block your seat with a payment of INR 10,000 to enroll in the program. Begin with your Prep course and start your Data Science journey!

Program Fee

Program Price INR 49,000 ( $750 ) + 18% GST

 

No Cost EMI options available*

PROGRAM BENEFITS

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Get this Data Science Master Program while working

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Industry recognized certificate from IBM

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28% annual growth in job openings

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Bygrad JobAssist™

 
 

Batch Start Dates

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Online

28ᵗʰ  Aug 2021

Frequently Ask Questions

What is the Executive Data Science Master Program with Bygrad?


The Executive Master Program is an engaging yet rigorous 06-month online program designed specifically for working professionals to develop practical knowledge and skills, establish a professional network, and accelerate entry into data science careers. The certification is awarded by IBM.




What will be the impact of Data Science in 2021?


Data science is an essential part of any industry today and will continue to be, given the massive amounts of data produced. Meaning both data and the demand for Data Science professionals is only going to rise.




Will the program Bygrad JobAssist™


Our preparation, you will get a great deal of project work and an \"Ability Score\" (figured based on your execution all through different stages). We at that point forward your project work and ability Score to organizations, your projects fill in as a proof (portfolio) of your range of abilities which when joined with our ability Score gives them a far-reaching examination of your insight identified with your activity profile. Organizations don't get this sort of investigation or straightforwardness anywhere else, and subsequently, they get you hired. Additionally, they get a confirmation that they are not employing a new kid on the block but rather a trained professional who will be productive from day one.




How do I earn the post graduate program certificate


Post successful completion of the program, you will get two certificates - one for the training and another for your project work.




How does refund or money back work in case I am not placed


Although it will not likely to happen to see our past success rate. We will try every inch of our efforts to place you. However, in case if we fail to do so, we will refund the fee directly into your bank account within 6 months of your course completion date. No questions asked. Click here for more details.




Is there any minimum educational qualification required to take this program?


Although we believe that skills are enough to get you hired, however, some companies hiring for Data Scientist profile in the industry will expect following out of you.

FRESH GRAD OR A COLLEGE STUDENT
A degree in B.Tech/M.Tech (Any Trade), BCA, MCA or B.Sc (Statistics or Mathematics), BA (Maths or Economics or Stats), B.Com.

WORKING PROFESSIONAL

Professional experience of 1+ years in Python, R, SAS, Business intelligence, Data warehousing, SQL. If your professional experience is not related to data analytics, you can still make a switch to Data scientist provided that you hold any of the degrees specified above.




What are last placement record?


Please be assured, we were able to place our last 3 batches with a minimum package of 4.3 lakh, an average package of 5.5 lakh and the highest package of 15.3 lakh.




What is covered under the 24/7 Support promise?


We offer 24/7 support through email, chat, and calls. We have a dedicated team that provides on-demand assistance through our community forum. What’s more, you will have lifetime access to the community forum, even after completion of your Data Science Course.




What are the top job roles in the field of Data Science?


Data Scientist is named the sexiest job of the 21st century and for all the right reasons - the opportunities, salary potential, demand, and more. Following which, other Data Science job roles are in demand too: Data Analyst, Business Analyst, Data Engineer, and Data Architect.




I am not from a technical background. Can I still join this Data Science Course?


Yes, you can join the Data Science PG Program even if you do not belong to a technical background. However, having a basic knowledge of programming languages and mathematics will be beneficial. We will teach you maths and stats at a very beginner level.