Skill Accelerator Program
Professional Program in Data Science
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Professional Program in Data Science
Program Outcomes
Elevate your career with Data Science Skills
Become a Data Scientist
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Understand the landscape of data science from a business, technical, and conceptual perspective.
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Master nuanced data analysis techniques using Inferential Statistics, Python, and SQL.
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Learn to design and develop Machine Learning models aligned with business objectives.
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Gain foundational knowledge in Generative AI, including prompt engineering with LLMs for natural language analysis.
Key program highlights
Why choose the Data Science program
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Hands-on, industry-relevant program
Gain practical experience with 25+ case studies, 2 projects, and 12 live sessions led by industry experts.
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Unparalleled learning support
Access 24/7 AI-powered support, dedicated Program Managers, expert forums, personalized feedback, and career assistance.
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Unique mentored learning model
Collaborate on hands-on practical applications in interactive, small-group sessions tailored to your profile, led by professional data scientists.
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Pathway to PG Certificate by UT Austin
Advance with interconnected courses and get a $750 fee waiver for the PG program in Data Science & Business Analytics.
Skills you will learn
Python
Exploratory Data Analysis
Business Statistics
Supervised Learning
Linear Regression
Model Deployment
GenAI
SQL
Python
Exploratory Data Analysis
Business Statistics
Supervised Learning
Linear Regression
Model Deployment
GenAI
SQL
- Overview
- Learning Journey
- Curriculum
- Projects
- Tools
- Certificate
- Faculty
- Mentors
- Career support
- Fees
This Data Science Program is ideal for
Professionals who want to leverage Data science skills to accelerate their careers
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Mid to senior professionals
Experienced professionals seeking to apply Data Science solutions to their existing business problems.
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Aspiring data science professionals
Individuals looking to transition into Data Science and build a strong technical career in the field.
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Business managers and leaders
Professionals aiming to lead teams for application and implementation of data science solutions.
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Tech professionals
Professionals in technical roles who want to advance their skills and integrate data science into their work applications.
Experience a unique learning journey
Our pedagogy is designed to ensure career growth and transformation
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Learn with self-paced videos
Learn critical concepts from video lectures by faculty & data science experts
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Engage with your mentors
Clarify your doubts and gain practical skills during the weekend mentorship sessions
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Work on hands-on projects
Work on projects to apply the concepts & tools learnt in the module
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Get personalized assistance
Our dedicated program managers will support you whenever you need
Program Curriculum
The curriculum is designed in such a way that learners can familiarize themselves with the concepts of data science and business analytics necessary to establish their career or transition to a career in the field of data science.
Pre-Work: Introduction to Data Science
This course provides you with an understanding of the evolution of Data Science over time, its application in industries, the mathematics and statistics behind them, and an overview of the life cycle of building data-driven solutions.
- The Fascinating History of Data Science
- Transforming Industries through Data Science
- The Math and Stats underlying the technology
- Navigating the Data Science Lifecycle
Pre-Work: Python
This course provides you with a fundamental understanding of the basics of Python programming and builds a strong foundation of the basics of coding to build Data Science applications.
- Introduction to Python Programming
- Data Science Application Case Study
Course 01: Python and Statistics Foundations
This course teaches you how to read, explore, manipulate, and visualize data to tell stories, solve business problems, and deliver actionable insights and business recommendations by performing exploratory data analysis using some of the most widely used Python packages.
Additionally, it equips you with the skills to perform statistical analysis, evaluate the reliability of business estimates using confidence intervals, test hypotheses, and analyze data distributions to make informed decisions before committing resources.
- Data Value Chain
- Python Programming
- Python for Data Science
- Exploratory Data Analysis
- Inferential Statistics Foundations
- Project - 1
Course 02: Machine Learning
This course helps you explore linear models to capture the relationships between variables and a known outcome that is continuous, check the statistical validity of the models, and draw statistical inferences to gain business insights regarding key factors influencing decision-making.
- Introduction to Supervised Learning- Linear Regression
- Decision Trees
- Bagging and Random Forest
- Project - 2
Course 03: Generative AI Foundations
In this course, you will explore Generative AI and its applications, gaining a clear understanding of the differences between generative and discriminative models to address real-world business challenges. Through interactive, hands-on exercises, you will also master SQL concepts by utilizing Generative AI to retrieve, filter, and analyze data with efficiency and precision.
- Introduction to Generative AI
- Introduction to Prompt Engineering
Course 04: Introduction to SQL
This course will help you gain an understanding of the core concepts of databases and SQL, gain practical experience writing simple SQL queries to filter, manipulate, and retrieve data from relational databases, and utilize complex SQL queries with joins, window functions, and subqueries for data extraction and manipulation to solve real-world data problems and extract actionable business insights.
- Week 1: Querying Data with SQL
- Week 2: Advanced Querying
Masterclass: Model Deployment
This masterclass will help you comprehend the role of model deployment in realizing the value of an ML model and how to build and deploy an application using Python.
LVC: Introduction to Model Deployment
Model deployment is the process of making a trained machine learning model accessible to a wider audience by operationalizing it. This module introduces participants to model deployment, provides an overview of its need in generating business value from ML models, and serializing and deploying ML models using Python libraries like Streamlit.
(Introduction to Model Deployment, Serialization, Deployment using Streamlit)
Self-paced Courses
Data Visualization using Tableau
In this course, you will learn how to read, explore, and effectively visualize data using Tableau and tell stories by analyzing data using Tableau dashboards.
- Storytelling with Data
- Creating Interactive Dashboards
Time Series Forecasting
In this course, you will learn how to describe components of a time series data and analyze them using special techniques and methods for time series forecasting.
- Introduction to Time Series Analysis
- Introduction to Forecasting
- ARIMA & SARIMA
Work on hands-on projects & case-studies
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2
hands-on projects
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25+
case studies
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12+
online mentorship sessions
FOOD AND BEVERAGES
FoodHub Order Analysis
About the Project
Perform an exploratory data analysis and provide actionable insights for a food aggregator company to get a fair idea about the demand of different restaurants and cuisines, which will help them enhance their customer experience and improve the business
Skills you will learn
- Python
- Numpy
- Pandas
- Seaborn
- Univariate Analysis
- Bivariate Analysis
- Exploratory Data Analysis
- Business Recommendations
Hospitality
Revenue Optimization for INN Hotels
About the Project
Analyze the data of INN Hotels to find which factors have a high influence on booking cancellations, build a predictive model that can predict which booking is going to be canceled in advance, and help in formulating profitable policies for cancellations and refunds.
Skills you will learn
- Exploratory Data Analysis
- Data Preprocessing
- Logistic regression
- Multicollinearity
- Decision trees
- Pruning
- Feature Importance
Manufacturing
Machine Predictive Maintenance
About the Project
Analyze the data of an auto component manufacturing company and develop a predictive model to detect potential machine failures, determine the most influencing factors on machine health, and provide recommendations for cost optimization to the managements
Skills you will learn
- Exploratory Data Analysis
- Data Visualization
- Decision trees
- Pruning
- Scikit-Learn
BFSI
Predicting Credit Card Eligibility for Bank Partnerships
About the Project
Analyze the data provided by a consultation firm that partners with banks, answer key questions provided, draw actionable insights, and help the company to improve the business by identifying the attributes of customers eligible for a credit card
Skills you will learn
- Exploratory Data Analysis
- Data Visualization
- Pandas
- Seaborn
Healthcare
Diabetes Risk Prediction
About the Project
Analyze the historical patient data provided and build a predictive model to help identify whether a person is at risk of diabetes or not
Skills you will learn
- Exploratory Data Analysis
- Data Visualization
- Bagging
- Random Forests
- Scikit-Learn
Master in-demand Data Science tools
Get data science training with in-demand tools to enhance your workflow, optimize models, and build data science solutions
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Python
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Pandas
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NumPy
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Seaborn
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Matplotlib
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Statsmodels
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Scipy
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Skitlearn
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Hugging Face
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ChatGPT
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SQL
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Tableau
Certificate of Completion by Great Learning
Get a certificate of completion in Professional Program in Data Science by Great Learning
* Image for illustration only. Certificate subject to change.
Meet your faculty
Meet our expert faculty-professionals with in-depth data science knowledge and a passion to help you succeed
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Dr. Abhinanda Sarkar
Academic Director - Data Science & Machine Learning
30+ years of experience in data science, ML, and analytics.
Ph.D. from Stanford, taught at MIT, ISI, and IIM Bangalore.
Know More
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Dr. Pavankumar Gurazada
Faculty for Business and AI Programs, Great Learning
15+ years of experience in marketing, digital marketing, and machine learning.
Ph.D. from IIM Lucknow; MBA from IIM Bangalore; IIT Bombay graduate.
Know More
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Prof. Mukesh Rao
Director, Academics, Great Learning
20+ years of expertise in AI, machine learning, and analytics
Director - Academics at Great Learning
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Mr. Udit Mehrotra
Data Scientist, Stripe
10+ years of experience in data science
Former Data Scientist at Mc.Kinsey & Company, Dell
Know More
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Mr. R Vivekanand
Co-Founder and Director
Expert in data visualization and marketing econometrics with 10+ years
Qualified Tableau trainer passionate about teaching business analytics
Know More
LinkedIn Profile
University LinkInteract with our mentors
Interact with experienced data science experts who will guide you in your learning & career journey
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Prabhat Bhattarai
Data Scientist Apple
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Olayinka Fadahunsi
Head of Data Science and Engineering
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Dale Seema
Data Science Specialist FNB
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Paolo Esquivel
Senior Data Scientist
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Eren Zedeli
Senior Data Scientist Smartsheet
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Monisha Sadhwani
Senior Analytics Consultant Fractal
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Faraaz Sheriff
Data Scientist Children, Community and Social Services, Ontario
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Yogesh Singh
Founder and CEO, NSArrows
Get dedicated career support
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1:1 career sessions
Interact personally with industry professionals to get valuable insights and guidance
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Interview preparation
Get an insiders perspective to understand what recruiters are looking for
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Resume & Profile review
Get your resume and LinkedIn profile reviewed by our experts to highlight your skills & projects
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E-portfolio
Build an industry-ready portfolio to showcase your mastery of skills and tools
Course fees
The Data Science course fee is 750 USD
Start learning for just 250 USD.
Invest in your Data Science career
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Understand the landscape of data science from a business, technical, and conceptual perspective.
-
Master nuanced data analysis techniques using Inferential Statistics, Python, and SQL.
-
Learn to design and develop Machine Learning models aligned with business objectives.
-
Gain foundational knowledge in Generative AI, including prompt engineering with LLMs for natural language analysis.
Batch Start Date
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Online · To be announced
Admissions Open
Batch Profile
The PGP-Artificial Intelligence and Machine Learning class consists of working professionals from excellent organizations and backgrounds maintaining an impressive diversity across work experience, roles and industries.
Industry Diversity
Educational background
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