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Explore Data Science Courses

Build a strong foundation with the best data science courses to boost your career. You will get a top-notch learning experience with these Popular Data Science Certificate Programs. These programs are in collaboration with world-class universities.

Career Transitions in Data Science

Check our learners' successful transitions in management job roles. Talk to our experts to understand how our programs can help you in your career goals.

483% hike

Kamini Sahu

Data Science

Business Development Executive

Dynamo Consulting Services Limited

Associate Business Analyst

Cotiviti
Sneha Jaiswal

Data Science

Teacher Partner

Cuemath

Data Processing Analyst

NielsenIQ
Abdul Rauf Mohammad

Data Science

Product Owner

JPMorgan Chase & Co.

Vice President

Wells Fargo
192% hike

Rajat Dekate

Data Science

Entrepreneur

MMKR POLYPLAST PVT. LTD.

Associate Business Analyst

Cotiviti
Dhivya Karthic

Data Science

Education Program Manager

IIT Madras | IIM Bangalore

Analyst

Deloitte Consulting
131% hike

Rishi Tiwari

Data Science

Assistant Manager

Zerodha Broking Limited

Data Analyst

Reliance Retail
92% hike

Siddharth Shinde

Data Science

Process Associate

Genpact

Data Analyst

Dell
133% hike

Ajit Muthunarayanan S

Data Science

Digital content associate

Amazon

Business Analyst

HCL
74% hike

Ajay Devdas Pananchikal

Data Science

DATABASE ADMINISTRATOR

Larsen And Toubro Infotech

Product Analyst

Big Basket
125% hike

Ann Maria John

Data Science

Drug Safety Associate

IQVIA RDS (India) Private Limited

Business Analyst

Genpact
87% hike

Akansha Pruthi

Data Science

Process Associate

Genpact

Research Analyst

Indegene
Aditya Sabbisetti

Data Science

Data Analyst

Makemytrip

Data Analyst

Walt Disney
35% hike

Akash Sah

Data Science

Senior System Engineer

Infosys

Associate Consultant

EY India
33% hike

Amulya Manne

Data Science

SPS Associate - SME

Amazon.com

Data Analyst

Myntra
83% hike

Akshaya N

Data Science

Product specialist

Zomentum

Business Reporting Analyst

EXL
Abhishek Pal

Data Science

Manager - Analytics and Market Research

Silvermine Group

Senior Analytics Advisor

EY

Know Our Data Science Courses

Introduction to Data Science Courses

The Best Course for Data Science

Data Science Course Syllabus (Curriculum)

Data Science Courses Faculty

Data Science Course Subjects

Universities Offering Data Science Courses

Data Science Course Eligibility

UT Austin's Data Science Courses Offered in Partnership with Great Learning

MIT Data Science Courses Offered in Partnership with Great Learning

What is the best data science course for a beginner in 2024?

Introduction to Data Science Courses

The ever-growing importance of data in today’s business landscape makes Data Science courses a must for anyone looking to start or further their career. Data Science courses offer people the opportunity to learn the ins and outs of Data Mining, Modeling, and Analysis, giving them the skills they need to make data-driven decisions in their chosen field.

Data Science courses help people to develop the skills and knowledge necessary to become successful professionals in this discipline. In addition to learning the theory behind Data Science, these courses also provide people with practical experience working with data. This experience is essential for people who want to pursue careers in Data Science, as it helps them to understand how to use data to solve real-world problems effectively.

In addition to the technical skills gained in these courses, people will also develop soft skills, such as problem-solving and critical thinking, which are essential in any business role. With the insights gained from these courses, businesses can make more informed decisions, leading to improved efficiency and profitability.

Anyone looking for a comprehensive introduction to Data Science will find plenty of courses to choose from. These courses from Great Learning cover everything from the basics of Statistical Analysis and Machine Learning to more specific topics like Data Visualization, Data Analytics, and Data Mining.

Types of Data Science Courses:

1. Data Science Online Courses

Learning Data Science online gives you the flexibility to learn at your own pace and fit your studies around your work and other commitments. You’ll also have access to a wealth of online resources, including video tutorials, lectures, and forums where you can ask questions and get feedback from fellow students and instructors.

Here is the list of Data Science courses offered online by Great Learning in Collaboration with Universities:

The Best Course for Data Science

Great Learning’s most popular Data Science courses include a Master’s Degree in Data Science, a PG Certificate in Data Science, a Professional Certificate, or taking Bootcamp courses in Data Science. It really depends on what you are looking for and what you hope to gain from pursuing Data Science. Below is the list of Data Science courses offered by Great Learning:

Data Science Course Syllabus (Curriculum)

The Data Science course syllabus at Great Learning provides the skills you need to become a successful Data Scientist, Data Analyst, Business Analyst, Data Engineer, and many more. You will learn the fundamental Data Science concepts, tools, and techniques. You will learn to use Python, SQL, and R for Data Analysis and visualize and interpret data for gathering insights. The course covers Regression and Prediction, Machine Learning techniques, and much more. You will also complete Capstone Projects to hone your practical skills and implement them in the industry.

Data Science Courses Faculty

The faculty team of our Data Science courses comprises top academicians in Data Science, along with numerous other skilled industry practitioners from leading universities and organizations that practice this cutting-edge domain.

Data Science Course Subjects

Before enrolling, it is usually advised to thoroughly understand the course syllabus, enabling you to determine whether the course equips you with the required skills. The subjects involved in Data Science are as follows:

Subjects	Subject Description
Introduction	It will provide a brief description of the Data Science course and the significance of Data Science in the industry.
Programming Languages	You will learn programming languages such as Python, R, and SQL for Data Analysis, Data Wrangling, Data Visualization, and Machine Learning.
Statistics	You will understand how to analyze data sets to draw insights and make predictions.
Data Mining	It introduces you to Data Mining, including a brief overview of the different techniques and approaches, such as Clustering, Decision Trees, and Neural Networks.
Machine Learning	You will learn about the different types of Machine Learning algorithms and how to train, test, and deploy them in real-world applications.
Time Series Forecasting	You will learn how to identify and model time series patterns and use these models to make forecasts in decision-making.
Big Data	You will also learn about the tools and techniques that Data Science professionals use to make sense of Big Data.
Data Analytics	It will cover the different types of Data Analytics techniques, including Exploratory Data Analysis, Predictive Modeling, and Prescriptive Analytics, which can benefit businesses.
Business Analytics	You will understand the process of analyzing data to gain insights that help businesses make better decisions.
Data Visualization	You will learn how to create and interpret data visualizations and use them to communicate data effectively.

Universities Offering Data Science Courses

If you’re looking to learn Data Science from the world’s top-ranked universities, you’ve come to the right place. The courses are offered by:

Massachusetts Institute of Technology - Institute for Data, Systems, and Society (MIT IDSS)
The University of Texas at Austin (UT Austin) McCombs School of Business
Northwestern University School of Professional Studies
Deakin University
Great Lakes Executive Learning

With multiple options available, you’re sure to find a course that meets your requirements.

Data Science Course Eligibility

Below are the eligibility requirements for a range of data science courses:

Course	Eligibility*
PGP - Data Science and Business Analytics	The program is best suited for: Freshers are early career professionals. Aspiring data science professionals Executives wanting to expand their knowledge and expertise in the data science domain. Experienced professionals who want to stay competitive in the ever-evolving technology industry. Professionals and managers without technical background.
PGP - Data Science and Engineering (PGP-DSE)	Applicants should have 60% or above in X, XII and a bachelor’s degree. The program is open for candidates in their final semester and recent graduates with 0-3 years of experience. Ideal for candidates with graduation in a quantitative discipline like engineering, mathematics, commerce, science, statistics, economics, etc.
PGP in Data Science and Engineering (Bootcamp)	Applicants should have 60% or above in X, XII and a bachelor’s degree. The program is open for candidates in their final semester and recent graduates with 0-3 years of experience. Ideal for candidates with graduation in a quantitative discipline like engineering, mathematics, commerce, science, statistics, economics, etc.
Data Science and Machine Learning Program	This program is for: Data Scientists, Data Analysts, and working professionals who wish to extract actionable insights from large volumes of data. Early career professional and senior managers. For those who have some academic/professional training in applied mathematics/statistics.
Master’s in Data Science	Students should have completed a 4 year U.S. bachelor’s degree or equivalent. For students who did not complete their degree in the U.S.: If your transcript evaluation states that your degree is equivalent to a 4 year U.S. bachelor degree then you can apply for this programme. If the student completed their bachelor degree in the U.S.: If you have a 4 year bachelor’s degree then you can apply.
Applied Data Science Program - (International Program)	This program is for Professionals interested in Data Science and machine learning careers. Professionals interested in leading Data Science and machine learning initiatives in their companies. Entrepreneurs interested in innovation using Data Science and Machine Learning.
Master of Data Science (Global)	Applicants must hold a bachelor's degree (minimum 3-year program) in a related field or a bachelor's degree in any discipline with at least 2 years of professional work experience. The applicants must meet Deakin University’s minimal English language requirement.
M.Tech in Data Science and Machine Learning (PES University)	Applicants must possess a Degree in B.E/B.Tech/M.Sc (Mathematics)/MCA from a recognized institution or university. They must have secured at least 50% in their pursued degrees. By the commencement of the program, applicants must have completed a minimum of 24 months of work experience.
Master of Science in Business Analytics (Eller College of Management)	The program is for: Young early career professionals looking to go abroad and master data-driven decision making for the business. Mid and senior-level professionals who are looking to go abroad and stay up to date with the latest business analytics skills needed for success in the digital world. Professionals who wish to transition to a Business Analytics career with industry-ready skills and knowledge.
MS Data Analytics (Walsh College)	Applicants must hold a 3 or 4-year bachelor’s degree or equivalent in any discipline with a minimum of 60% marks from a UGC-recognized university or institution. The medium of instruction must be in English. No GRE/GMAT or any English proficiency test scores are required. Note: Candidates should score a minimum of 2.75 GPA in the 1st year to be eligible for 2nd year on campus at Walsh College.
M. Sc. in Big Data and Business Analytics (FOM International University)	Candidates with either a B.Tech (Any Stream), B.E (Any Stream), BCA, B.Sc. IT, B.Sc. Maths or Stats are eligible to apply for this programme. No work experience is required. English proficiency test [IELTS/TOEFL/PTE score is required]. Note: Please speak with your learning consultant for more details. Great Learning provides English proficiency test preparation service at no additional cost.

*Please visit the respective program page for detailed information on the eligibility criteria.

UT Austin's Data Science Courses Offered in Partnership with Great Learning

UT Austin's Data Science Courses Offered in Partnership with Great Learning.

In collaboration with Great Learning, the University of Texas at Austin offers a range of comprehensive online data science certificate courses. These programs are designed for professionals and are tailored to accelerate your professional growth. Depending on the program format, these programs provide a data science certificate online and offline.

Program Name	Learning Mode	Focus Area
PG Program in Data Science and Business Analytics	Online	Data Science & Business Analytics
Data Analytics Essentials	Online	Data Analytics

These programs are designed to be flexible and accessible, offering mentored online learning experiences that cater to mid-career professionals. They provide a blend of theoretical knowledge and practical skills, preparing you for the evolving demands of the tech industry.

MIT Data Science Courses Offered in Partnership with Great Learning

MIT Data Science Courses Offered in Partnership with Great Learning.

Massachusetts Institute of Technology (MIT), in partnership with Great Learning, offers a variety of in-depth online postgraduate certificate programs specifically designed for professionals seeking to enhance their careers. These programs emphasize key areas in data science and technology, ensuring participants are well-equipped for the dynamic demands of the industry.

Program Name	Learning Mode	Focus Area
MIT Data Science and Machine Learning Program	Online	Data Science & Machine Learning
MIT Applied Data Science Program	Online	Applied Data Science
MIT IDSS's Data Science and Machine Learning Program	Online	Data Science and Machine Learning

These MIT programs, facilitated through Great Learning, are structured to offer flexibility and convenience, making them ideal for mid-career professionals. The courses blend theoretical insights with practical applications, preparing participants for the rapidly evolving landscape of the data science and technology sectors.

What is the best data science course for a beginner in 2024?

For a fresher in 2024, there are several top-notch data science courses offered by Great Learning. They are listed below:

Data Analytics Course for Beginners - The University of Texas, Austin (For Non- Indian learners)
PGP in Data Science (Online) - Great Lakes Executive Learning (For Indian Learners Only)
PGP in Data Science (Bootcamp) - Great Lakes Executive Learning (For Indian Learners Only)

Essential Building Blocks for Data Science

Data Science Course Faculty

Learn from the top faculty in the field of data science

Dr. Daniel A Mitchell

Phd (University of Maryland)

Clinical Assistant Professor - Department of Information, Risk & Operations Management

Thomas W. Miller

Faculty Director, Data Science, Northwestern University

Bikram Ghosh

Associate Professor of Marketing, Eller Fellow

Dr. Abhinanda Sarkar

Ph.D. from Stanford University, Ex-Faculty - MIT

Faculty Director, Great Learning

Dr. Ian McCulloh

Faculty Leader in AI and Strategy, Johns Hopkins University

Dr. Kumar Muthuraman

PHD (Stanford University)

Faculty Director - Centre for Research and Analytics
20+ Years Work Experience

Devavrat Shah

MIT

Professor, EECS and IDSS, MIT

Edward Arroyo

Faculty, School of Professional Studies at Northwestern University

Munther Dahleh

MIT

Program Faculty Director, MIT Institute for Data, Systems, and Society (IDSS)

Javad Katibai

Chassis System Architect - General Motors

Jesper Nielsen

Associate Professor of Marketing

Dr. Jacob Dearmon

Professor of Economics

Dr. Jones Mathew

Principal and Head of Institution, Professor- Marketing, Great Lakes

Shreenidhi Bharadwaj

Professor - Data Science

Eyran Gisches

Senior Lecturer in Management Information Systems Manager, Organizational Behavior Laboratory

Carrie Dugan

Course Lead, School of Professional Studies at Northwestern University

John N. Tsitsiklis

MIT

Clarence J. Lebel Professor, Dept. of Electrical Engineering & Computer Science (EECS) at MIT

Dr. Dave Schippers

VP and Academic Dean

Shyam Sunder

Director, Dhaliwal-Reidy School of Accountancy. Lou Myers Professor of Accounting

Dr. Robert Greve

Associate Dean

Nethra Sambamoorthi

Faculty Lead - Foundations, Advanced Methods, Capstone

M. Gray Hunter

Senior Lecturer of Economics. Academic Director, MS Business Analytics Program. Pre-Business Statistics Coordinator

Dr. Abhinanda Sarkar

Ph.D. from Stanford University

Faculty Director, Great Learning

Caroline Uhler

Henry L. & Grace Doherty Associate Professor, EECS and IDSS, MIT

Donald Wedding

Faculty - Data Science at Northwestern University

Ankur Moitra

Rockwell International Career Development Associate Professor, Mathematics and IDSS, MIT

James Gerrity

PhD, Adjunct Associate Professor

Tiemen Woutersen

Professor of Economics, Eller Fellow

Dr. Loknath Ambati

Assistant Professor

Prof. Prashant Koparkar

Corporate Trainer and Consultant - Machine Learning

Kimberly Chulis

Adjunct Data Science Faculty at Northwestern University

Christopher Lamoureux

Diamond Professor of Finance

Prof. Raghavshyam Ramamurthy

MBA (Whitman School of Management)

Industry Expert in Visualization

Thomas Petz

CIO/COO, Assistant Professor of IT

Seokjun Youn

Assistant Professor of Management Information Systems

Dr. Justin Wareham

Assistant Professor of Management

Dr. Srabashi Basu

Professor, PhD Statistics

Mr. R Vivekanand

MBA (Monash University)

Co-Founder and Director

Stefanie Jegelka

MIT

X-Consortium Career Development Associate Professor, EECS and IDSS, MIT

David Gamarnik

Nanyang Technological University Professor of Operations Research, Sloan School of Management and IDSS, MIT

Christopher Heiden

Program Lead at IT, Associate Professor of Business Information Technology

Dr. Jabir Rahman

Assistant Professor

Prof. Snehamoy Mukherjee

Masters (IIT Kanpur)

Adjunct Faculty

Dr. Michael Williams

Professor of Marketing

Dr. C P Gupta

Finance

Dr. D Narayana

Professor, Artificial Intelligence and Machine Learning, Great Learning

Guy Bresler

Associate Professor, EECS and IDSS, MIT

Prof. Dr. P. K. Vishwanathan

Professor of Analytics, Great Lakes Institute of Management

Dr. P K Viswanathan

MBA (FMS, Delhi)

Professor, Analytics & Operations

Jonathan Kelner

Professor, Mathematics, MIT

Mr. Gurumoorthy Pattabiraman

MSc (Madras School of Economics)

Faculty, Data Science & ML, Great Learning

Prof. Dipayan Sarkar

Master in Economics (Karnatka University)

Consultant, Author, Visiting Faculty

Kalyan Veeramachaneni

Principal Research Scientist at the Laboratory for Information and Decision Systems, MIT.

Philippe Rigollet

Professor, Mathematics and IDSS, MIT

Dr. Rohit Kapoor

PHD (IIM Ahmedabad)

Associate Professor

Tamara Broderick

Associate Professor, EECS and IDSS, MIT.

Prof. Saurabh Aggarwal

B Tech (IIT, Delhi)

Professor, HBTI Kanpur

Victor Chernozhukov

Professor, Economics and IDSS, MIT

Mr. Krishna Mohan

MBA(Universtity of Cincinatti, Ohio)

Sr. Manager Technology

Mr. Vinit Thakur

M.S (University of Mumbai)

Visiting Faculty

Dr. Dan Mitchell

Assistant Professor, McCombs School of Business

Data Science Industry Mentors

Learn from highly skilled industry practitioners working with top-notch companies. Stay ahead of the curve and ensure you are learning the most relevant data science skills.

Serdar Cellat

Principal Data Scientist

Nitish Jaipuria

Strategist (Data Science)

Weibiao (Wilson) Huang

Analytics Consultant

Boston Consulting Group (Singapore)

Dale Seema

Data Science Specialist

Amit Jain

Deputy Manager - Business Analytics & Business Intelligence

Keppel Corporation Limited (Singapore)

Dr. Satish Raghavendran

Vice President, Deloitte

Vaibhav Verdhan

Analytics Leader, Global Advanced Analytics

Phumzile Phantsi

Data Scientist

ABSA Group (South Africa)

Adaikalavan Ramasamy

Senior Research Scientist

Genome Institute of Singapore (GIS)

Wole Ogungbesan

Director - Advance Analytics & Automation

UBS (United Kingdom)

Prabhat Bhattarai

Data Scientist

Mr. Bradford Tuckfield

Founder and Data Science Consultant

Mr. Manish Gupta

Senior Applied Scientist,Microsoft

Jeremy Samuelson

Principal Data Scientist & ML Engineer,

Surya Kunju

MarTech & Gen AI Lead,

Mr. V Shekhar Avasthy

Chief Data Scientist & Principal Consultant, Facts 'n' Data

G Anthony Reina

Head of Machine Learning,

Nikhila Kambalapalli

Consultant, Data Science

Ms. Mayan Murray

Senior Data Scientist and UX Consultant

Mr. Sreevasan P S

Data Science Practitioner, AI/ML Mentor, Ex - Cognizant

Dr. Sunil Kumar Vuppala

Director, Data Science,

Mr. Balaji Sundararaman

Mentor - Data Science, ML, AI and Analytics at Great Learning

Randhir Agarwal

Director, Data Science & Data Engineering,

Srihari Nagarajan

Senior Data Scientist

Mr. Vibhor Kaushik

Data Scientist

Mr. Udayakumar Devaraj

Senior Data Scientist, WNS

Olayinka Fadahunsi

Head of Data Science and Engineering

Mr. Amit Agarwal

Senior Data Scientist

Fahad Akbar

Senior Manager Data Science

Mr. Kemal Yilmaz

Senior Data Scientist

Anis Sharafoddini

Data Scientist Lead

Udit Mehrotra

Data Science Specialist

Ms. Xiaojun Su

Data Science Product Manager

Avinash Ramyead

Senior Quantitative UX Researcher / Data Scientist / Behavioral Scientist in Video ML

Shannon Schlueter

Director of Data Science

Mr. Juan Castillo

Machine Learning Engineer

Edward Krueger

Principal Data Scientist and Proprietor

Mr. Andrew Marlatt

Data Scientist - Revenue Expansion

Paolo Esquivel

Senior Data Scientist

Mr. Rohit Dixit

Senior Data Scientist

Michael Keith

Analytics Manager

Anuj Saini

Principal Data Scientist, RPX Corporation

Kalle Bylin

Product Engineer

Mr. Srikanth Pyaraka

Data Science Product Manager

Mohit Jain

Principal Data Scientist

Yogesh Singh

Founder and CEO, NSArrows

Mr. Angel Das

Data Science Consultant

Rushabh Shah

Software Developer, Kyra Solutions

Mr. Shirish Gupta

Lead Data Scientist

Marco De Virgilis

Actuarial Data Scientist Manager

Mr. Vanessa Afolabi

Senior Data Scientist

Roshan Santhosh

Data Scientist, Meta

Mr. Thinesh Pathmanathan

Data Scientist

Mr. Grivine Ochieng

Lead Data Engineer

Data Science Projects

Check out our learners' enthusiastic, career-transitioning projects and become a highly skilled Data Science professional.

Marketing

Airplane Passenger Satisfaction Prediction

Using the survey data, predict whether the customer will be satisfied or dissatisfied with the services that the Airlines is providing
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Entertainment

Movie Lens Data Exploration

The GroupLens Research Project is a research group in the Department of Computer Science and Engineering at the University of Minnesota. In this project, we will perform exploratory data analysis to understand the popularity trends of movie genres and derive patterns in movie viewership.
Learn more
Social Media

Facebook Comments Prediction

Using the attributes of a facebook post, including the number of people talking about the post, number of check-ins on the page, day of the week, etc, predict how many comments a Facebook post would get.
Learn more
Insurance

Insurance Claim Prediction

A key challenge for the insurance industry is to charge each customer an appropriate premium for the risk they represent. In this project, we will build a regression model to predict the cost of insurance claims using user information on age, gender, bmi, blood pressure, health conditions, as well as insurance claim details.
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Social + Healthcare

West Nile Virus Prediction

Given weather, location, testing, and spraying data, this competition asks you to predict when and where different species of mosquitoes will test positive for West Nile virus. A more accurate method of predicting outbreaks of West Nile virus in mosquitoes will help the City of Chicago and CPHD more efficiently and allocate resources towards preventing transmission of this potentially deadly virus.
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Telecom

Network Congestion Type Prediction

The telecom industry is faced by a common challenge of network congestions due to various factors. To solve this problem, we will use data usage information of mobile phones from various telecom companies and find out a relation between the features of the mobile phone service provider (eg => bytes consumed through various services, etc.) and types of network congestion.
Learn more
Insurance

Insurance Premium Default Propensity Prediction

Predict the probability that a customer will default on their premium payment, so that the insurance agent can proactively reach out to the policy holder to follow-up for the payment of premium
Learn more
Sales & Marketing

Forecasting Monthly Sales of French Champagne

Being able to make accurate predictions of future revenue can be hugely important for businesses. This project will focus on forecast the next monthly revenue of a french chamapagne brand, which will inform the decision-making process across all areas of the business, from purchasing decisions and marketing activity to staffing levels.
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Retail

Retail Sales Prediction

Predict the department-wide sales for each store for the following year and model the effects of mark-downs on holiday weeks. Based on your findings, provide recommended actions, with prioritization placed on largest business impact.
Learn more
Healthcare

COVID-19 Global Forecasting

The capstone project is a focused approach to attempt a real-life challenge with the learnings from the program. In this project, you will use a combination of various datasets and models to forecast and predict daily cases and deaths. You will also create various plots to gain insights and showcase your results. the data has been collected from different sources like WHO, WorldoMeters, 1Point3Arces and many more to understand various aspects and build relevant features to use in models.
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Banking

Loan Customer Identification

Identify potential loan customers for a bank using classification techniques and compare models to select the best performing one.
Learn more
E-Commerce

Product Recommendation System

Online E-commerce websites like Amazon use different recommendation models to provide different suggestions to different users. Amazon currently uses item-to-item collaborative filtering, which scales to massive data sets and produces high-quality recommendations in real-time. In this project, you will use similar concepts to create your own product recommendation system.
Learn more
HR

CEO Compensation

Examine the linkage between CEO compensation and company performance using the tools of descriptive and inferential statistics.
Learn more
Object Detection

Face Mask Segmentation

Predict and apply masks over the faces detected in images using Convoluted Neural Networks and image recognition algorithms. The goal of the project is to build a system that acts as a face detector to locate the position of a face in an image and apply a segmentation mask on the face. For this, we will utilise data from over 409 images and 1000 faces from the WIDER FACE dataset.
Learn more
Insurance

Insurance Data Visualization

Create interactive dashboards using Tableau’s data visualization tools to provide policy-level insights to the CEO of an insurance company.
Learn more
News & Media

Sarcasm Detection

Past studies in Sarcasm Detection mostly make use of Twitter datasets collected using hashtag based supervision, but such datasets are noisy in terms of labels and language. Furthermore, many tweets are replies to other tweets and detecting sarcasm in these requires the availability of contextual tweets. In this hands-on project, the goal is to build a model to detect whether a sentence is sarcastic or not, using Bidirectional LSTMs. The dataset is collected from two news websites, theonion.com and huffingtonpost.com.
Learn more

User Reviews & Testimonials

Explore learner’s testimonials from real people who transformed their careers with our Data Science courses.

Mauricio De Garay

MIT Professional Education's Applied Data Science Program
Berthy Buah

Data Science and Machine Learning: Making Data-Driven Decisions
Chun Wing Ip

Data Science and Machine Learning: Making Data-Driven Decisions
Kelechi Enyioha

Post Graduate Program in Data Science and Business Analytics
Brooks Christensen

MIT Professional Education's Applied Data Science Program
Mohammed Majdy

Post Graduate Program in Data Science and Business Analytics
Perci Olarte

Post Graduate Program in Data Science and Business Analytics
Flor de María Gómez Esparza

Post Graduate Program in Data Science and Business Analytics
Leanne Da Cerca

Post Graduate Program in Data Science and Business Analytics
Monica Suarez

Post Graduate Program in Data Science and Business Analytics

Webinars on Data Science

VIEW RECORDING

Learner Reviews on our Data Science Courses

Read these reviews from our real learners and their experience with our courses. This will help you choose the right course for yourself.

Ravinathan R

21 Aug 2024

Batch of | Associate Data Analyst at Sagility Indian private limited, Bangalore

I joined this program because I always wanted to explore the scope of Data Science across different fields such as healthcare, finance, etc. This program helped me understand how to solve complex data problems. The career support team guided me with tips to crack job interviews.

Program : PG Program in Data Science and Engineering

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Sunny Shekhar Singh

21 Aug 2024

Batch of | Supply Chain Data Analyst at Hewlett Packard

The program curriculum is well-planned. Great Learning’s faculty focus on teaching the basics first and then going for advanced topics. Their career guidance team also provides us with all the required guidance to successfully crack interviews. I landed a role at HP after completing the program.

Program : Post Graduate Program in Data Science and Business Analytics

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Kalaivani

21 Aug 2024

Batch of | Data Analyst at Indigo

This program gave me a new direction in my career. I was able to learn and apply Mathematical skills to building different Machine Learning models. And I leant how to effectively present those models as well. I am quite happy that I found a job even before completing the final examination.

Program : PG Program in Data Science and Engineering

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Mahathevan S J

21 Aug 2024

Batch of | Cost Control Specialist and Analyst at KBR Chennai

I did my PGDM in Data Science and Engineering from Great Learning. It has been a wonderful experience. I gained my knowledge and am very thankful to all the faculties and support staff for helping and patiently coping with me to get the knowledge transferred. I had a Great Learning.

Program : PG Program in Data Science and Engineering

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Sekhar Krovvidi

21 Aug 2024

Batch of | Assoc Engineer, Acquired Associate at Neustar

I always wanted to get into a role that required using multiple skills, and hence I chose Data Science. This program taught me in-depth about Machine Learning and several other relevant tools. The career support team guided me through job interview processes for different companies.

Program : PG Program in Data Science and Engineering

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Shubash A V

21 Aug 2024

Batch of | Data Analyst at SagasIT Analytics

My learning experience with Great Learning was truly amazing. I was eager to upskill my knowledge and stay on top of my field and the programs offered by Great Learning were just what I needed. I would highly recommend it to anyone who is looking to upskill and advance their career.

Program : PG Program in Data Science and Engineering

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SAI SATHISH M R

21 Aug 2024

Batch of | Software Development Engineer 2 at Modivcare

I extend my deepest gratitude to the Great Learning team for their invaluable support throughout our journey. The program’s experience was truly exceptional, fostering an environment that greatly enhanced my resilience. I found it remarkably supportive and conducive to learning.

Program : PG Program in Data Science and Engineering

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Manas Ghosh

21 Aug 2024

Batch of | Assistant Consultant at Tata Consultancy services

The program has not only advanced my career but also gave me a better understanding of how to solve problems. The well-structured curriculum, mentorship sessions, mock interviews, resume reviews, etc, all helped me successfully transition to Data Science.

Program : PG Program in Data Science and Engineering

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Nivedhitha.R

21 Aug 2024

Batch of | Knowledge Engineer at Elsevier

The coursework was very detailed and it aligned with the industry standards. The program helped me in paving the path as a Data Science professional. I would like to thank all the faculties who helped me in achieving my key milestones throughout my coursework.

Program : PG Program in Data Science and Engineering

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Pradeel Salkar

21 Aug 2024

Batch of | Project intern at Atomus Analytics

My experience in this program was truly remarkable. By dedicating myself and putting in the extra effort, I was successfully able to complete it. I would like to thank the entire Great Learning team for their unwavering support and guidance throughout my journey.

Program : PG Program in Data Science and Engineering

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Frequently Asked Questions

What is a Data Science Course?

The Data Science course is a fine blend of mathematics, statistical foundations and tools, and business acumen, all of which assist in extracting from raw data the hidden patterns or insights that can significantly aid in formulating essential business decisions. Proving prevalent in academics, Business Analytics courses are now an amalgamate of Data Science.

The major components of the course also include scientific computing, data structures and algorithms, data visualization and data analysis, and machine learning tools and techniques to escalate business performance. The course could be around six to twelve months, designed to give candidates a solid foundation in the discipline. In addition to educational materials, our Data Science certificate courses contain virtual laboratories, interactive quizzes and assignments, case studies, industrial projects, and capstone projects, which will accelerate your learning path.

What is the duration of the best Data Science programs?

The duration of Data Science programs at Great Learning varies from one program to another depending on the curriculum, institute, and so on. They range from 10 weeks to 6 months.

View all Data Science programs for the course duration.

What is the course fee for Data Science programs at Great Learning?

Like the course duration, the fee structure also varies from one program to another depending on the curriculum, institute, and so on.

View all Data Science courses for the fee structure.

Who would be the faculty teaching these online Data Science courses?

World-class, renowned academicians from the respective institutions would teach the online Data Science courses.

What are some of the best Data Science courses for students and working professionals?

All the Data Science programs from Great Learning are preferable for working professionals.

However, for students, we have designed the Post Graduate Program in Data Science and Business Analytics, where students learn the foundational skills of Data Science and Analytics. The curriculum covers Python programming language, Data Visualization, Data Analysis, Machine Learning techniques, Business Analytics skills, and much more.

How are the reviews of Data Science courses from Great Learning?

All our courses are top-class, acknowledged by several business leaders and top magazines. Most of our learners have accomplished successful career transitions into Data Scientist or Data Analyst roles.

Check out our learners’ testimonials who have completed our online Data Science courses.

Why should I opt for the online Data Science courses from Great Learning?

Great Learning and some of the world’s most reputed institutes have collaborated to offer learners the best Data Science programs in the industry, enabling them to gain a good understanding of it.

These Data Science programs offer numerous benefits, such as:

Customized Learning Journey
Hands-on Experiential Learning with Real-World Projects
Dedicated Program and Career Support
Result-Oriented Curriculum
Cohort-Based Pedagogy
Learning Analytics
First-Class Faculty and Mentors

Numerous other benefits are offered by Great Learning. Check out our Data Science courses for in-depth information.

What certifications will I receive after completing the online Data Science course?

You will receive certifications from the respective institutes, depending on your chosen course, such as UT Austin for Data Science and Business Analytics, MIT PE for Applied Data Science Program, etc.

What are some of the best Data Science courses available in the market?

Some of the best online Data Science courses available in the market are offered by Great Learning, in collaboration with some of the world’s renowned institutes. The programs are as follows:

Data Science and Business Analytics - The University of Texas at Austin
Applied Data Science Program - MIT Professional Education
Practical Decision Making using Data Science - National University of Singapore
Data Science and Machine Learning: Making Data-Driven Decisions - MIT IDSS

What is the salary of a data scientist fresher across the world?

With the increase in the demand for data scientists across the globe, salaries are also skyrocketing. Data scientists are making generous pay from top-notch companies. Since there is a lack of data science professionals in the field, even freshers are earning excellent salaries.

The following are a few salaries of a data scientist fresher from different countries:

Data scientist salary in the United States: USD 101K per annum
Data scientist salary in the United Kingdom: £55K per annum
Data scientist salary in India: ₹10.5 Lakh per annum
Data scientist salary in Germany: €55K per annum
Data scientist salary in Australia: AU$121K per annum

What are the career options in data science?

Choosing a job opportunity in data science gives you a lot of career options:

Data Scientist: Responsible for analyzing and interpreting complex data to help inform business decisions.
Data Analyst: Focuses on processing and performing statistical analyses on large datasets.
Machine Learning Engineer: Specializes in designing and implementing machine learning techniques, models and systems.
Data Engineer: Focuses on the preparation of 'big data' for analytical or operational uses.
Business Intelligence (BI) Analyst: Uses data to help organizations make better business decisions.
Data Science Manager/Lead: Ensures meeting organizational goals with various data science teams and projects.
Research Scientist: Engages in data-driven research, often in academic, government, or corporate settings.
Statistician: Applies statistical methods to collect, analyze, and interpret data to solve real-world problems in business, engineering, healthcare, or other fields.

What is the demand for data science jobs in 2024?

The demand for data science jobs is extremely high, and data is considered the new oil in today's digital economy. Companies across industries are seeking professionals who can interpret and analyze this data to provide business insights. Therefore, the demand for data science skills, including machine learning, predictive analytics, and data visualization, is rising significantly.

What is the future scope for data scientists?

The future scope for data scientists is promising. With the advent of AI and machine learning, companies in various sectors, such as healthcare, finance, retail, and e-commerce, are increasingly leveraging data to make informed business decisions, resulting in a growing demand for data scientists.

As per the U.S. Bureau of Labor Statistics, the future for data scientists is highly promising, with a 35% growth in employment from 2022 to 2032, which is higher than all the other occupations.

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Great Learning Academy enables you to learn fundamental tools, courses, and skills on trending technologies. This platform offers you some essential concepts on several topics in Data Science, AI & ML, and Big Data Analytics.