• Admission closes on 17 Apr, 2024
  • Program Duration 11 months
  • Learning Format Online Bootcamp

Why Join this Program

Purdue’s Academic Excellence

Purdue’s Academic Excellence

Data Science certificate from Purdue, the 8th most innovative university in the US.

Gain Generative AI Mastery

Gain Generative AI Mastery

Dedicated course on Generative AI, Prompt Engineering, ChatGPT and more

IBM’s Industry Prowess

IBM’s Industry Prowess

Obtain certificates for IBM courses and get access to masterclasses by IBM 

Hands-on Experience

Hands-on Experience

Acquire practical experience through 25+ hands-on projects and 20+ tools with integrated labs


Looking to enroll your employees into this program ?

Data Science in Liverpool Overview

Experience the excellence of Purdue's academic prowess through this Post Graduation in Data Science program. Delve into essential topics like Python, R, ML, Data Visualization, Generative AI, Explainable AI, ChatGPT, and more using an interactive learning approach with live sessions led by global experts. Elevate your data skills with us!

Key Features

  • Post Graduate Data Science certificate and Purdue alumni association membership
  • Generative AI and Prompt Engineering: Dedicated course with live sessions
  • Learn about ChatGPT, DALL-E, Midjourney & other prominent tools
  • Masterclasses delivered by Purdue faculty and IBM experts
  • Industry-relevant capstone projects in 3 domains
  • 25+ hands-on projects with seamless access to integrated labs
  • Exclusive hackathons and Ask Me Anything sessions by IBM
  • 8X higher engagement in live online classes by seasoned academics and industry professionals
Key Features
Post Graduate Data Science certificate and Purdue alumni association membership
Generative AI and Prompt Engineering: Dedicated course with live sessions
Learn about ChatGPT, DALL-E, Midjourney & other prominent tools
Masterclasses delivered by Purdue faculty and IBM experts
Industry-relevant capstone projects in 3 domains
25+ hands-on projects with seamless access to integrated labs
Exclusive hackathons and Ask Me Anything sessions by IBM
8X higher engagement in live online classes by seasoned academics and industry professionals

Data Science in Liverpool Advantage

Post Graduation in Data Science is an all-encompassing program in collaboration with Purdue University – leveraging Purdue's academic excellence in data science and Simplilearn's IBM partnership.

  • Purdue Certification

    Partnering with Purdue University

    • Receive a joint Purdue-Simplilearn certificate
    • Masterclasses by Purdue faculty
    • Purdue Alumni Association membership
  • IBM Certification

    Program in collaboration with IBM

    • Industry recognized IBM certificates for IBM courses
    • Industry masterclasses conducted by IBM
    • Exclusive hackathons and Ask Me Anything (AMA) Sessions with IBM leadership

Data Science in Liverpool Details

Embark on a carefully designed learning journey with this Post Graduation in Data Science program covering Generative AI, Explainable AI, prompt engineering, ChatGPT, statistics, Python, data analysis, ML, data visualization, and more. Elevate your data science skills and propel your career forward.

Learning Path

  • Get started with the Post Graduate Program in Data Science in partnership with Purdue University Online and explore everything about the domain. Kickstart your Data Science journey with the preparatory courses on Statistics and Programming.

    • Develop a comprehensive understanding of coordinate geometry and linear algebra.
    • Comprehend the concepts of eigenvalues, eigenvectors, and eigendecomposition.
    • Build a strong foundation in calculus, including limits, derivatives, and integrals.
    • Comprehend the differences between structured and unstructured data.
    • Explore statistical measures such as means, medians, deciles, percentiles, modes, and quartiles.
    • Define measures of dispersion and other statistical indicators, such as range, quartile deviation, and outliers.
    • Describe mean absolute deviation (MAD), standard deviation, and variance.
    • Acquire proficiency in both procedural and object-oriented programming.
    • Recognize the advantages and benefits of using Python as a programming language.
    • Install Python and its integrated development environment.
    • Familiarize yourself with the Jupyter Notebook and its practical applications.
    • Implement Python identifiers, indentations, and comments effectively.
    • Understand Python's data types, operators, and string functions.
    • Learn about the various types of loops in Python.
    • Explore the concept of variable scope within functions.
    • Explain the principles and characteristics of object-oriented programming.
    • Develop a comprehensive understanding of databases and their relationships.
    • Learn how to use standard query tools and work with SQL commands.
    • Master transactions, table creation, and views for efficient database management.
    • Comprehend and execute stored procedures to perform complex operations.
    • Acquire expertise in various SQL lessons, including filtering, ordering, aliasing, aggregate commands, grouping, conditional statements, joins, subqueries, views, and indexing.
    • Understand user access control functions to ensure database security.
    • Create your first Python program using variables, strings, functions, loops, and conditions.

    • Understand and apply concepts related to lists, sets, dictionaries, conditions, branching, objects, and classes in Python.

    • Utilize the Pandas library to load, manipulate, and save data and read and write files in Python.

    • Explore the processes of data preparation, model building, and evaluation.
    • Develop a strong understanding of NumPy and its applications, including array indexing and slicing techniques.
    • Gain a clear understanding of statistical concepts like skewness, covariance, and correlation.
    • Examine different hypothesis tests, including Z-test, T-test, and ANOVA.
    • Work with pandas' two primary data structures: Series and DataFrame.
    • Utilize pandas for data loading, indexing, reindexing, and data merging.
    • Create compelling visualizations using Matplotlib, Seaborn, Plotly, and Bokeh.
    • Analyze the machine learning pipeline and gain a comprehensive understanding of essential operations involved in machine learning operations (MLOps).
    • Explore supervised learning and unsupervised learning methods.
    • Analyze different regression models and identify their suitability for specific scenarios.
    • Identify linearity between variables and create correlation maps.
    • Examine different ensemble modeling techniques, such as bagging, boosting, and stacking.
    • Evaluate and compare different machine learning frameworks, including TensorFlow and Keras.
    • Build a recommendation engine using PyTorch.
    • Acquire expertise in various visualization techniques, such as heat maps, treemaps, waterfall charts, and Pareto charts.
    • Skillfully work with filters, parameters, and sets to manipulate data effectively.
    • Become proficient in utilizing special field types and Tableau-generated fields and creating and employing parameters.
    • Learn how to construct different charts, interactive dashboards, and captivating story interfaces.
    • Gain proficiency in data blending, creating extracts, and efficiently organizing and formatting data.
    • Master various calculations, including arithmetic, logical, table, and level of detail (LOD) expressions.
  • The data science capstone project provides a valuable opportunity to apply the skills you have acquired during this program. With the guidance of dedicated mentors, you will address a real-world data science problem aligned with industry standards. This comprehensive project covers data processing, model building, and reporting business results and insights. It is the final step in your learning journey and enables you to demonstrate your Data Science expertise to potential employers.

  • Attend an online interactive masterclass and get insights about advancements in technology/techniques in Data Science, AI, and Machine Learning.

  • Attend this online interactive industry master class to gain insights about Data Science advancements and AI techniques.

    • Understand the meaning of business analytics and its importance in the industry 
    • Grasp the fundamentals of Excel analytics functions and conditional formatting 
    • Learn how to analyze complex data sets using pivot tables and slicers 
    • Apply statistical tools and concepts such as moving averages, hypothesis testing, ANOVA, and regression to data sets using Excel 
    • Represent your findings using charts and dashboards
    • Learn to analyze data and extract valuable business insights using Microsoft Power BI.
    • Create interactive dashboards
    • Gain skills to use Power BI to address and solve various business challenges
    • Improve operational efficiency and effectiveness
    • Learn how to develop dashboards from published reports.
    • The course covers using Quick Insights to discover valuable patterns in data rapidly.
    • The course provides valuable troubleshooting techniques
    • Understand the fundamentals of artificial intelligence and generative AI models
    • Comprehend the concept of explainable AI, recognize its significance, and identify different approaches
    • Gain an understanding of ChatGPT, including its working mechanisms, notable features, and limitations
    • Identify and explore diverse applications and use cases where ChatGPT
    • Gain exposure to fine-tuning techniques to customize and optimize ChatGPT models 
    • Recognize the ethical challenges of generative AI models and ChatGPT
    • Gain insights into the future of generative AI and its challenges.
    • Learn about math, variables, strings, vectors, factors, and vector operations
    • Gain fundamental knowledge of arrays and matrices, lists, and data frames
    • Get insight into conditions and loops, functions in R, objects, classes, and debugging
    • Learn how to read text, CSV, and Excel files accurately and how to write and save data objects in R to a file
    • Understand and work on strings and dates in R

Skills Covered

  • Generative AI
  • Prompt Engineering
  • ChatGPT
  • Explainable AI
  • Large Language Models
  • Explainable AI
  • Conversational AI
  • Exploratory Data Analysis
  • Descriptive Statistics
  • Inferential Statistics
  • Model Building and Fine Tuning
  • Supervised and Unsupervised Learning
  • Ensemble Learning
  • Data Visualization
  • Database Management

Tools Covered

ChatGPTDalle.2Mid-journeyNumPypandaspythonSciPyMatPlotlibtableauMicrosoft ExcelMySQLFSD

Industry Project

  • Project 1

    Sales Analysis

    Utilize Python to analyze a clothing company’s sales data for Australia, and state by state help the company make data-driven decisions for the coming year.

  • Project 2

    Employee Performance Analysis

    Create ML programs to understand different factors for employee turnover. Implement various ML techniques for analyzing performance and suggest employee retention strategies.

  • Project 3

    Classification of Songs

    Perform exploratory data analysis and cluster analysis to create cohorts of songs. Use this classification to build an efficient recommendation system.

  • Project 4

    Creation of an Interactive Sales Dashboard

    Create an interactive Sales Dashboard for an apparel OEM in Tableau for the Sales department to use for ad-hoc analysis and reporting.

  • Project 5

    Crime Analysis with Tableau Dashboard

    Prepare a dashboard to keep the police department and the city updated on the statistics of crime events. You are required to create a dashboard/story using Tableau.

  • Project 6

    Marketing Strategies with Exploratory Data Analysis

    Perform exploratory data analysis and hypothesis testing. The goal is to gain a better understanding of the various factors that contribute to customer acquisition.

  • Project 7

    Develop Ecommerce app with Python

    Develop an e-commerce app on the Python platform that could categorize, add or remove items from the cart and support different payment options

  • Project 8

    Weather Prediction

    Create a classification model using ten years of rainfall data to predict the weather for different locations across Australia

  • Project 9

    Credit Card Fraud Analysis

    Utilize data science and machine learning methodologies. Identify fraudulent credit card transactions so that the end customers are not charged for items that they did not purchase

Disclaimer - The projects have been built leveraging real publicly available data-sets of the mentioned organizations.


Program Advisors and Trainers

Program Advisors

  • Patrick J. Wolfe

    Patrick J. Wolfe

    Frederick L. Hovde Dean of the College of Science at Purdue University

    Patrick J. Wolfe, an award-winning researcher in the mathematical foundations of data science, is the Frederick L. Hovde Dean of the College of Science at Purdue University and was named the 2018 Distinguished Lecturer in Data Science by the IEEE.


Program Trainers

  • Simon Travasoli

    Simon Travasoli

    25+ years of experience

    Senior Data Science Consultant at Citi Bank

  • Armando Galeana

    Armando Galeana

    20+ years of experience

    Founder and CEO, Ubhuru Technologies

  • Prashant Nair

    Prashant Nair

    20+ years of experience

    Solution Architect | Data Scientist

  • Nikhil Garg

    Nikhil Garg

    16 + years of experience

    Data Science Instructor


Join the Data Science industry

The global Data Science Platform Market size was valued USD 95.3 billion in 2021, The market for data science platform is estimated to reach 322.9 USD billion in 2026.

Job Icon28%

Annual Job Growth By 2026

Source: Market Research Rpt
Job Icon11.5 M

Expected New Jobs For Data Science By 2026

Source: US bureau of Labor
Job Icon$86K - $157K

 Average Annual Salary

Source: Glassdoor

Batch Profile

This Post Graduation in Data Science Program is designed for working individuals from various sectors. The variety of students enriches class discussions and interactions.

  • The class consists of learners from excellent organizations and diverse industries
    Information Technology - 41%Consulting - 20%Manufacturing - 8%Pharma & Healthcare - 8%BFSI - 8%Others - 15%
     course learners from Citigroup, Liverpool
     course learners from PricewaterhouseCoopers, Liverpool
     course learners from Tata Consultancy Services, Liverpool
     course learners from Abbott, Liverpool
     course learners from Bosch, Liverpool
     course learners from GE Aviation, Liverpool
     course learners from Accenture, Liverpool
     course learners from Ernst & Young, Liverpool
     course learners from VMware, Liverpool
     course learners from Amazon, Liverpool
     course learners from Nvidia, Liverpool
     course learners from Dell, Liverpool
  • The class maintains an impressive diversity across work experience and roles
    Designation Breakup
    Associate - 21%Midlevel - 47%Senior-level - 24%Executive - 8%
    Total Years of Experience
    Less than 3 years - 16%3-5 years - 15%5-8 years - 11%8+ years - 58%
  • The class has learners with varied educational qualifications from excellent institutions
    Bachelors - 53%Masters - 29%Post Graduates - 3%Others - 15%
     course learners from BITS Pilani, Liverpool
     course learners from IIM Kozhikode, Liverpool
     course learners from HULT International Business School, Liverpool
     course learners from IIM Indore, Liverpool
     course learners from IIT Bombay, Liverpool
     course learners from University of Illinois at Chicago, Liverpool
     course learners from McGill University, Liverpool
     course learners from Oklahoma State University, Liverpool
     course learners from IIT Roorkee, Liverpool
     course learners from AIIMS, Liverpool
     course learners from NITIE, Liverpool
     course learners from Northern Illinois University, Liverpool

Alumni Review

The prevalence of big data in business decisions makes this a valuable course for working professionals and executives. This comprehensive online boot camp curriculum includes Business Intelligence/ Data Analytics, Natural Language Processing, Business Analytics, and Deep Learning.

John Scott

VP of Global Finance Technology & InnovationWalmart

What other learners are saying

Admission Details

Application Process

Candidates can apply to this Post Graduation in Data Science Program in 3 steps. Selected candidates receive an offer of admission, which is accepted by admission fee payment.


Submit Application

Tell us why you want to enroll in the Post Graduate Program in Data Science


Application Review

An admission panel will shortlist candidates based on their application



Selected candidates can start within 1-2 weeks

Eligibility Criteria

For admission to Post Graduation in Data Science, candidates should have:

2+ years of work experience preferred
A bachelor's degree with an average of 50% or higher marks
Basic understanding of programming concepts and mathematics

Admission Fee & Financing

The admission fee for this Post Graduation in Data Science is £ 2,790. This fee covers applicable program charges and the Purdue Alumni Association membership fee.

Financing Options

We are dedicated to making our programs accessible. We are committed to helping you find a way to budget for this program and offer a variety of financing options to make it more economical.

Pay in Installments

You can pay monthly installments for Post Graduate Programs using Splitit payment option with 0% interest and no hidden fees.


Financing Options

We provide the following options for one-time payment

  • Credit Card
  • Paypal

£ 2,790

Apply Now

Program Benefits

  • Masterclasses delivered by Purdue and IBM
  • Earn program completion certificate
  • Exposure to ChatGPT, Generative AI, Explainable AI and more
  • Alumni Association Membership from Purdue University
  • Simplilearn’s Career Assistance post program completion

Program Cohorts

Next Cohort

    • Date


      Batch Type

    • Program Induction

      6 May, 2024

      14:30 BST

    • Regular Classes

      11 May, 2024 - 1 Dec, 2024

      14:30 - 18:30 BST

      Weekend (Sat - Sun)

Got questions regarding upcoming cohort dates?

Data Science in Liverpool FAQs

  • What is the eligibility criteria for this Purdue Data Science Program?

    • This Purdue Data Science Program requires the following qualifications:

      • A bachelor's degree with a 50% or above grade point average.

      • Understanding basic programming principles and mathematics is required.

      • Working professionals with at least two years of experience are recommended for Purdue Data Science Program.

  • Is there a minimal educational need to be considered for this Purdue Data Science Program?

    If you want to participate in this Purdue Data Science Program, you must have a bachelor's degree with a 50 percent (or above) average.

  • What is the admission process for this Purdue Data Science Program?

    • There are three manageable phases to the Purdue Data Science Program admission:

      • All interested applicants must apply online using the application form.

      • Candidates will be shortlisted by an admissions panel based on their application.

      • The shortlisted candidates will get an offer of admission, which they must accept by paying the fees.

  • What does Data Science entail?

    Data science studies large amounts of data using cutting-edge tools and methodologies to uncover hidden patterns, extract useful information, and make business choices.

  • What influence will Data Science have in 2024?

    Given the vast volumes of data created today, data science will continue to be essential for any company. As a result, both data and the need for Data Scientists will continue to increase.

  • What are the most common Data Science job roles?

    The most in-demand job of the twenty-first century is Data Scientist, and for all the right reasons: the opportunity, earning potential, demand, and more. Other job oriented courses and Data Science career positions are in high order: Data Engineer, Data Architect, Data Analyst, and Business Analyst

  • What are the essential functions and responsibilities of a Data Scientist?

    A Data Scientist identifies the business issues that need to be answered and then develops and tests new algorithms for quicker and more accurate data analytics utilizing a range of technologies such as Tableau, Python, Hive, and others. A Data Scientist also collects, integrates, and analyses data to acquire insights and reduce data issues so that strategies and prediction models may be developed.

  • What is a Data Science Professional's earning potential?

    The field's potential is endless, and Data Science jobs provide many opportunities and high-paying incomes. Based on experience, region, and employer, India's typical Data Scientist compensation might range from Rs.1,000K to Rs.1,800K. (according to Glassdoor) The annual wage in the United States ranges from $113K to $150K. Discover other professional courses here.

    Discover Your Future: Find More Business Intelligence Courses to Shape Your Career.

  • What are the financial aids available to enroll in this Purdue Data Science Program?

    We have partnered with Affirm to provide competitive financing options(EMI option available) 

  • What can I achieve from this Purdue Data Science Program?

    You will receive the following as part of this Purdue Data Science Program, which is offered in conjunction with IBM:

    • Simplilearn-Purdue University Joint Certificate.

    • Industry-recognized certificates from IBM (for IBM courses) and Simplilearn

    • Purdue Alumni Association membership eligibility

    • Lifetime access to all (the core) of the e-learning content created by Simplilearn

  • After finishing the Purdue Data Science Program, what credential will I receive?

    Simplilearn and Purdue University will grant you a joint certification upon completing the Purdue Data Science Program. After completing the courses on the learning route, you will get industry-recognized credentials from IBM and Simplilearn.

  • Will there be any materials to help you get started with this Purdue Data Science Program?

    You'll have access to a preparatory course once you pay the first installment of the fee. Before attending the first class, you must complete the prescribed learning path. The tutorials will include 8-10 hours of video-based self-paced learning content.

  • What exactly is Global Teaching Assistance?

    Our teaching assistants are a devoted group of subject matter experts who are here to help you pass the Data Science exam on your first try. From class onboarding through project mentorship and employment aid, they engage students proactively to ensure that the course route is followed and help you expand your learning opportunity.

  • How will my doubts/questions be addressed in the admission process?

    We have a specialized staff of admissions counselors that can assist you with your application for this Purdue Data Science Program.

  • What are the qualifications of the faculties, and how are they chosen?

    Our highly skilled Data Science professors are all industry specialists with years of expertise. Before they are qualified to train for us, they have undergone a thorough selection procedure that includes profile screening, technical Examination, and a training demo. We also ensure that only trainers with a high alumni rating stay on our staff.

  • How can I get the certificate?

    You will be qualified for the certificate if you meet the following minimum criteria. This certificate will attest to your abilities as a Data Science specialist.

    Course Course completion certificate Criteria
    Programming Refresher Required 85% of Online Self Paced completion
    Statistics Essential for Data Science Required
    Data Science with R Required
    1. 85% of online self-paced completion or attendance of 1 live virtual classroom,
    2. a score above 75% in the course-end assessment,
    3. and successful evaluation in at least 1 project
    Data Science with Python Required
    Machine Learning and Tableau Required
    Natural Language Processing Required
    Capstone Project Required Attendance of 1 live virtual classroom and successful completion of the capstone project

  • Will I be able to access the content after completion of the Purdue Data Science Program?

    Yes, even after completing the Purdue Data Science Program, you may access the course content.

  • How to know whether this Purdue Data Science Program is good for me?

    It's always beneficial to learn new talents and broaden your knowledge. This Purdue Data Science Program was created in collaboration with Purdue University and is an excellent combination of a world-renowned curriculum and industry-aligned training, making this Post Graduate Program a superb choice

  • Is it possible to sign up in this Purdue Data Science Program if I have no prior experience with the subject?

    Yes, even if you have no prior understanding of Data Science, you may enroll in the Purdue Data Science Program since it will take you from the foundations to the top. You will gain all of the high fundamental Data Science abilities.

  • My present position does not need me to work with data. Is it logical for me to pursue this Purdue Data Science Program?

    Data rules businesses all around the world. The more data-driven you are, the better off your company will be. Using data insights, you can make meaningful decisions, create strategies, and help your organization accomplish its goals faster. Enrolling in this comprehensive Data Science curriculum will undoubtedly provide you with a competitive advantage

  • What does the 24/7 Support guarantee cover?

    We provide email, chat, and phone help around the clock. We have a dedicated staff that provides on-demand support through our community forum. Furthermore, you will have lifelong access to the discussion forum, even when your course is completed.

  • Can I obtain a refund if I wish to discontinue my enrollment?

    If required, you can easily cancel your enrollment. After deducting an administration charge, we will reimburse the money. Please view our Refund Policy for more information.

  • Disclaimer

    The Purdue Data Science Program is offered on a non-credit basis and is not transferable to a degree

  • Can I get a sealed transcript for World Education Services (WES) at the end?

    These certifications and do not include any transcripts for WES, this is reserved only for degree programs. We do not offer sealed transcripts and hence, our programs are not applicable for WES or similar services.

  • What are the key learning outcomes of the course “Essentials of Generative AI, Prompt Engineering and ChatGPT?

    Through this course, you will gain a holistic understanding of the essentials of generative AI and its landscape, prompt engineering, Explainable AI, Conversational AI, ChatGPT and other LLMs.

    The key learning objectives of this course are: 

    • Understand the fundamentals of Generative AI models, including the working principles and various Gen AI models.

    • Comprehend the concept of Explainable AI, recognize its significance and identify different approaches to achieve explainability in AI systems.

    • Apply effective prompt engineering techniques to improve the performance and control the behavior of Generative AI models.

    • Understand ChatGPT, including its working mechanisms, notable features and limitations.

    • Identify and explore diverse applications and use cases where ChatGPT can be leveraged.

    • Gain exposure to fine-tuning techniques to customize and optimize ChatGPT models 

    • Recognize the ethical challenges of generative AI models and ChatGPT to ensure responsible data usage, mitigate bias and prevent misuse. 

    • Understand the potential of Generative AI to revolutionize industries and explore prominent generative AI tools. 

    • Gain insights into the future of Generative AI, its challenges and the steps needed to unlock its full potential.

  • What key topics are covered in the course “Essentials of Generative AI, Prompt Engineering and ChatGPT”?

    Some of the key topics covered in the course “Essentials of Generative AI, Prompt Engineering and ChatGPT” are: 

    • Generative AI and its Landscape 

    • Explainable AI 

    • Conversational AI 

    • Prompt Engineering 

    • Designing and Generating Effective Prompts 

    • Large Language Models 

    • ChatGPT and its Applications

    • Fine-tuning ChatGPT 

    • Ethical Considerations in Generative AI Models 

    • Responsible Data Usage and Privacy 

    • The Future of Generative AI 

    • AI Technologies for Innovation 

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  • Disclaimer
  • PMP, PMI, PMBOK, CAPM, PgMP, PfMP, ACP, PBA, RMP, SP, and OPM3 are registered marks of the Project Management Institute, Inc.