Placement stats

70000+ Career Transition

12LPA Exciting salaries

52% Average Salary Hike

650+ Hiring Partners

Companies that trust upGrad learners

This Bootcamp Will Uplift Your Career. Here’s How.

395+ blended learning hours

Learn from World Class Data Scientists and International Data Science Publishers to become job ready

Immersive learning platform

Get reports on strengths and weaknesses on tech skills through coding on CloudLabs

20+ projects and case studies

Learn over 20 tools and technologies through real life industry projects

Outcome driven pedagogy

Career coaching includes mock interviews, CV, LinkedIn, Github and soft skills training

10X more employable

Get access to 10X more job opportunities and get ahead of your peers

16+ hours of group career coaching

Become trained to join the workforce through interactions with tech industry leaders

Get a certificate of completion on an Intensive Bootcamp from upGrad

Certificate

Program creators

David Haertzen

David Haertzen

Big Data Analytics Leader, InfoGoal LLC

Ex-3M, Allianz Life

  • Exp - 33 Years
Denis Rothman

Denis Rothman

AI Author, Speaker, and Instructor

Ex-IBM

  • Exp - 31 Years
Jeffrey Aven

Jeffrey Aven

Principal Consultant Gamma Data

Big Data Solutions

  • Exp - 26 Years
Gopikrishnan R

Gopikrishnan R

Co-Founder and CTO, CrosInfo Software Pvt Ltd

Ex-IBM, Airtel

  • Exp - 23 Years
Peter Henstock

Peter Henstock

Machine Learning & AI Lead, Pfizer

Pfizer, Ex-Harvard

  • Exp - 21 Years
Beau - Carnes

Beau - Carnes

Director of Technology Education, freeCodeCamp

Ex-ElevatorUp

  • Exp - 21 Years
Jignesh Kariya

Jignesh Kariya

Sr. Database Consultant, HM Revenue & Customs

Ex-Deutsche

  • Exp - 21 Years
Ashish Gulati

Ashish Gulati

Python & Data Science Consultant, Tower Research Capita

Ex-Dell, Flipkart

  • Exp - 20 Years
Shobhit Nigam

Shobhit Nigam

Program Director - Data Science & Engineering

Knowledgehut upGrad

  • Exp - 18 Years
Phillip Kinn

Phillip Kinn

Senior Data Scientist, E. & J. Gallo Winery

Ex-Bank of America

  • Exp - 17 Years
Mark Strefford

Mark Strefford

Founder and CTO, Timelaps AI Limited

Ex-Capgemini

  • Exp - 15 Years
Emmanuel Segui

Emmanuel Segui

Asst. Director, Reporting and Programming, Univ of Alabama

University of Alabama

  • Exp - 15 Years
Rahul Tiwari

Rahul Tiwari

Data Scientist and Co-Founder, TheScholar

Ex-Deloitte

  • Exp - 15 Years
Dr. Vishwakarma J.S.

Dr. Vishwakarma J.S.

Chief Technology Officer, Aeries

Ex-Volkwagen, PWC, EY

  • Exp - 14 Years
George Mount

George Mount

Founder, Stringfest Analytics

Stringfest Analytics

  • Exp - 14 Years
Enes Bilgin

Enes Bilgin

Staff Machine Learning Engineer, Argo AI

Ex-Microsoft, Amazon

  • Exp - 13 Years
Jeremiah Lobo

Jeremiah Lobo

Data Visualization Lead, Bank of America

Ex-Capgemini, Bank of America

  • Exp - 13 Years
Marie Stephen Leo

Marie Stephen Leo

Director of Data Science APAC, Edelman Data & Intelligence

Sephora

  • Exp - 12+ Years
Mo Medwani

Mo Medwani

Adjunct Faculty - Data Science & Analytics, Mercer University

Ex-CDC, RBS

  • Exp - 12+ Years
Harish Masand

Harish Masand

Project Manager - Digital Enablement (Data and AI), Hewlett Packard Enterprise

Hewlett Packard

  • Exp - 12 Years
Anatoly Zelenin

Anatoly Zelenin

Freelance Trainer - Apache Kafka

Anatoly Zelenin

  • Exp - 11 Years
Rashmi Banthi

Rashmi Banthi

Data Scientist, AArete

Ex-Harvard, Pfizer

  • Exp - 10 Years
Bradford Tuckfield

Bradford Tuckfield

Data Science Instructor and Consultant

Ex-American Express

  • Exp - 10 Years
Malvik Vaghadia

Malvik Vaghadia

Principal Consultant - Data and Analytics, NTT DATA

NTT Data, Ex-EY

  • Exp - 10 Years
Avery Smith

Avery Smith

Data Scientist, Data Career Jumpstart

Ex-Exxonmobil

  • Exp - 7 Years
Rocky Jagtiani

Rocky Jagtiani

Master Data Science ML and AI trainer and Project Consultant to RTI CAG( Central Govt )

Suven Consultants and Technology Pvt.Ltd.

  • Exp - 16 Years
Manikant Kandukuri

Manikant Kandukuri

Senior Data Scientist

Ex Axis Solar

  • Exp - 11 Years
Jayanth MK

Jayanth MK

Data Science Engineer at Siemens Technology

Siemens Technology India

  • Exp - 4 Years
Urvinder Singh

Urvinder Singh

Data Scientist at Colgate-Palmolive DnA CoE | 2xGCP Certified | Mentor- Data Science & Tableau

Colgate-Palmolive

  • Exp - 13 Years
Tushit Dave

Tushit Dave

Data Science Consultant @ HCL | NLP | Keynote Speaker | Trainer & Coach | Author & Content Creator | MLOPS | Analytical Experimentor | Data manipulator | Strategist | Story Teller and in the end Theory Matter

HCL

  • Exp - 10 Years

Learn with a world class curriculum

Module-1

Mastering MS Excel and Concepts of Programing

Week 1-2

This module helps you take your first steps towards becoming a successful Data Scientist. You will be introduced to the fundamentals of MS Excel, Learn about formatting concepts, formulas and Statistical Analysis using Excel, Learn the meaning and utility of algorithms, loops, and flow charts, Understand how computers, operating systems,and the World Wide Web works.

Topics Covered

  • Discovering MS Excel
  • Understanding Programming Basics
Module-2

Discovering Data Analysis

Week 3-13

In this module you will learn how to store, manipulate, and retrieve the data along with the advanced visualisation techniques using Matplotlib, Seaborn and Plotly. You will master converting the raw data into high order operations and perform analysis using NumPy and Pandas.

Topics Covered

  • Discovering SQL Basics and mastering Data Analysis
  • Understanding Python for DS - Installation, Building Blocks, Strings and Data Structures
  • Grasping Python for DS - Functions, Modules, Files, Lambda functions, Errors and OOPs
  • Discerning Probability and Statistics - Descriptive Statistics, Distributions and Probability Theory
  • Mastering Probability and Statistics - Hypothesis Testing, Regressions and ANOVA
  • Grasping Data Preprocessing - Numpy, Pandas, RegEx
  • Discovering Data Preprocessing - Web Scraping and EDA
  • Mastering NoSQL
  • Discerning Data Visualization with Tableau
Module-3

Understanding Machine Learning with Python

Week 14-20

During this module you'll learn about linear algebra and calculus and their applications in Data Science, You'll also get a comprehensive understanding of Machine Learning, Linear Regression, Naïve Bayes and Support Vector Machine along with understanding the difference between Bagging and Boosting in Machine Learning.

Topics Covered

  • Grasping Machine Learning - Math for DS
  • Discovering Machine Learning - Linear Regression
  • Understanding Regularization Techniques - LASSO and RIDGE
  • Introduction to Classification and Logistic Regression
  • Discovering KNN, Naive Bayes and SVM
  • Mastering Decision Tree, Random Forest and Boosting
  • Grasping Unsupervised Learning - Clustering and PCA
Module-4

Data Engineering

Week 21-24

Discover the various elements of the Hadoop Ecosystem and how they can be used to solve Big Dataproblems. Understand how Relational Data Processing works in Spark and perform real-time Stream Processing Using Apache Spark and with Amazon Kinesis. You will then get a thorough understanding of Spark SQL and Understand how to deploy Machine Learning models to make inferences using Amazon SageMaker.

Topics Covered

  • Grasping Big Data Processing with Hadoop
  • Discovering Streaming Big Data with Spark
  • Mastering Streaming Big Data with Spark
  • Mastering Machine Learning Model Deployment on Cloud
Module-5

NLP and Deep Learning

Week 25-27

This module strengthen your fundamentals of Natural Language Processing (NLP) and provides the hands-on experience with TextBlob and then Spacy. You will be performing sentimental analysis and creating chatbots and gain in depth understanding of Deep Learning, TensorFlow, and how Neural Networks work. You will also gain the exposure of understanding the application of AI in the real world.

Topics Covered

  • Discovering NLP - Feature Extraction, Texblob, Spacy, Text Classification
  • Grasping NLP - Sentiment Analysis and Chatbots
  • Discerning Deep Learning with Keras and Tensorflow - Keras, Tensorflow and CNN
  • Mastering Deep Learning with Keras and TensorFlow, Adv CNNs, NLP and GANs
Module-6

Data Structures and Algorithms with Career Support

Week 28

Explore the fundamentals techniques of Algorithm Analysis, Linked Lists and Binary Trees. You will also learn about the Advanced Data Structures and how to analyze the Asymptotic Performance of Algorithms. Learn Algorithmic Design Paradigms and Methods of Analysis and Microservices Architecture and its Implications.

Topics Covered

  • Basic Techniques of Algorithm Analysis
  • Linked Lists and Binary Trees
  • Advanced Data Structures
  • Analyze the Asymptotic Performance of Algorithms
  • Algorithmic Design Paradigms and Methods of Analysis
  • Microservices Architecture and its Implications

Get a real world understanding through industry projects

NutriGro
NutriGro

Food and Drink

Build intelligence to predict user’s healthiness based on past grocery orders and recommend healthier options.

AnomaData
AnomaData

Manufacturing

Build intelligence to understand the health of machinery using Machine Learning and predict anomaly data/events.

MoodForMusic
MoodForMusic

Music

Building an application that detects the mood using still images or videos and recommends the music accordingly.

For-Rest from Fires
For-Rest from Fires

Tools

Build intelligence using Convolutional Neural Networks to detect fire accidents in buildings and forests.

Propensify
Propensify

Business

Build a Propensity Model to learn how likely certain target groups customers may act under certain circumstances.

VoiceBox
VoiceBox

Productivity

Build your own virtual voice assistant using NLP and Python (on similar lines of Alexa and Siri).

DocAssist
DocAssist

Health and Fitness

Build intelligence to analyse patient data to help doctors decide the best treatment.

SrapIt
SrapIt

Business

Build intelligence using Machine Learning to predict the scrap percentage in manufacturing.

Recommender
Recommender

Shopping

Build intelligence to help customers discover products they may like and most likely purchase.

ByDefault
ByDefault

Banking and Finance

Build a Credit Risk Modelling Application via Machine Learning to predict a customer's creditworthiness.

Tools and Technologies covered

The upGrad Advantage

Video Course Bootcamps upGrad

Cloud Labs

Industry projects

Interview Opportunity

Career guidance sessions

Performance Report

Top Product Companies Instructors

Admission Process

Pricing Plans

Scholarships upto INR 10,000
1. Upfront Payment
INR 70,000 + GST INR 1,55,000 + GST
EMI Partners
Tenure (Monthly) Interest (Flat) Per Annum EMI
6 0.00% INR - 12,783
9 10.25% INR - 9,178
12 10.25% INR - 7,129
18 10.25% INR - 4,974
24 10.25% INR - 3,896
Tenure (Monthly) Interest (Flat) Per Annum EMI
6 0.00% INR - 12,783
9 10.00% INR - 9,161
12 10.00% INR - 7,113
18 10.00% INR - 4,958
24 10.00% INR - 3,880
  • The credit facility is provided by a third party credit facility provider and any arrangement with such third party is outside upGrad's purview.
  • A processing fee will be charged on the basis of the payment method selected.
  • ₹ 5,000 as Downpayment has to be paid before the program begins.
  • Standard Interest-based EMI Plans of Propelld have Reduced interest rates mentioned are approx. 10 -10.25% flat rate for 10% flat rate for Propelld.
  • Standard Interest based EMI plans for Liquiloans mentioned is Flat interest Rates.
  • Interest Rate is subjected to the market scenario.
2. Pay After Placement
INR 48,000 + GST Upfront Payment
+
8% of CTC + GST Pay After Placement
Paid at the time of enrollment  INR 48,000
Pay After you get a tech job 8% of CTC
Monthly payments during the course    INR 0   
Monthly payments after starting new job  0.67% of CTC 
Total Cost  INR 48,000 + 8% of CTC + GST
*Taxes are applicable
3. Bundled Program (Data Science + Gen AI)
INR 1,50,000 + GST INR 3,10,000 + GST
EMI Partners
Tenure (Monthly) Interest (Flat) Per Annum EMI
6 0.00% INR - 27,833
9 0.00% INR - 18,556
12 0.00% INR - 13,917
18 10.25% INR - 10,704
24 10.25% INR - 8,385
Tenure (Monthly) Interest (Flat) Per Annum EMI
6 0.00% INR - 27,833
9 0.00% INR - 18,556
12 0.00% INR - 13,917
18 9.00% INR - 10,530
24 9.00% INR - 8,211
  • The credit facility is provided by a third party credit facility provider and any arrangement with such third party is outside upGrad's purview.
  • A processing fee will be charged on the basis of the payment method selected.
  • ₹ 10,000 as Downpayment has to be paid before the program begins.
  • Interest Rate is subjected to the market scenario.

See what our learners say

Bhupendra Choudhary

Bhupendra Choudhary

My overall journey has been great. My mentor and trainer have been super supportive. They help everyone in the batch follow the curriculum... Show More

Amrita Surensra Bimal

Amrita Surensra Bimal

I enjoyed this Data Science program a lot. Most importantly for me, I learnt about Python and Data engineering-related Big Data tools... Show More

Brajesh Chotia

Brajesh Chotia

I relish live, online sessions and understanding the content in detail. I learnt Python and Data Analysis via this program... Show More

Vaibhav Sah

Vaibhav Sah

After 8 years of journey, I have always been looking for continuing my studies. Then after comparing through multiple options, I finally chose... Show More

Nandish Swarup

Nandish Swarup

My journey at upgrade has been nothing but a rollercoaster ride full of fun and excitement. I was looking for ways to add some skills to my skill set...Show More

Austin Bernard

Austin Bernard

While looking to upskill myself, I found Upgrad. It was a tremendous journey over the last year. The program has helped change my perceptions... Show More

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Frequently Asked Questions

1. What is the prerequisite to join the program?

There is no prerequisite for the Data Science Bootcamp. Even without any prior programming or analytics expertise, learners can enroll in this bootcamp that features best-in-class live training, plenty of hands-on exercises and assignments with Cloud Lab.

2. What kind of jobs can I expect as a working professional from non-technical backgrounds?

The program will train you to apply for roles like Data Scientist, Data Analyst, Business Analyst, Big Data Engineer, Statistician, Business Intelligence Developer. That said, the outcome entirely depends on the time you dedicate to this course.

3. Does non-tech experience count as work experience?

Yes, any form of work experience, irrespective of the roles you are currently in, will be considered as work experience.

4. What is the format of the qualifying test?

The qualifying test will check your logical reasoning and English language skills (as the mode of instruction is in English).

5. What if I fail the entry test?

Not to worry. You have one more chance to reappear for the entry test.

6. What is the medium of instruction?

Medium of instruction and program delivery is 100% English and we expect candidates to know English as a mandatory language to apply for the program.

7. Can someone who has a gap after graduation and doesn’t have a job at present, apply to the program?

Yes, you can still apply for the program.

8. What if I do not have an Indian government identity proof?

At the time of admission, having an Indian government identity is mandatory.

1. How many live sessions do I have to attend?

There would be live sessions conducted on the weekends. To successfully complete the program, you need to attend at least 80% of these sessions.

2. Do I have the option to fast-track this program?

We want all our learners to pursue the curriculum we have designed for you to gain an entry into the world of full stack development. There are no shortcuts to this program.

3. Can I opt for a job by myself?

upGrad’s programs are recognized by the industry. You surely can apply to any company by creating an impressive resume with industry projects.

4. Do I need to sign any documents for getting a job?

You just need to go through our T&C and accept it to be eligible for placements.

5. Will I receive the certificate after program completion?

Yes, you will receive the program completion certificate considering that the exit criteria is met by the student as per policy.

6. Do I have to take the first job I am offered?

No. But our obligation to get an invitation for the inteview will end with the first job offer you receive.

7. The course hours do not work for me. Can I attend classes in my own time?

No. It is mandatory for students to attend lectures as per defined program schedule and required to maintain 80% attendance for all live deliverables (lectures, mentorship calls).

8. What is the program duration and career services period?

Program duration is of 6 months. Career services period starts post successful completion of the progam and is of 6 months duration.

1. Can I get any special discount for this program?

We are offering you this program at competitive rates. Hence, we are not offering any discounts, however, we have a lot of financing options to support you to do this program.

2. What financing options do I have?

We have EMI options with financial institutions for flexible tenures.

3. What are the documents required for opting for an EMI?

Each loan partner would have a different set of documentation requirements for the EMI. upGrad SPOC will guide you through the admission process.

4. Are there interest or processing fee charges on EMI?

The user will have to bear standard charges as applicable as per loan partner policy.

5. Is there any down payment to block the seat?

Yes, you need to pay a block amount to confirm your enrollment in the program

1. How does the Interview Opportunity Program work?

The Guaranteed Interview Opportunity Program provides prospective learners from partner companies with a clear path to earn an interview. Each company requires that learners complete the program requirements outlined by upGrad.

  • Prospective learners that have met the criteria will be provided an opportunity to interview with the partner companies.

  • Qualified learners should will be contacted by upGrad's placement team during the 6th month or within six months following successful program completion.

Support

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