Our Purdue Program Duration and Fees

Purdue programs typically range from a few weeks to several months, with fees varying based on program and institution.

Program NameDurationFees
Post Graduate Program in AI and Machine Learning

Cohort Starts: 16 Sep, 2024

11 months$ 4,300
Post Graduate Program in Data Science

Cohort Starts: 16 Sep, 2024

11 months$ 3,800
Applied Generative AI Specialization

Cohort Starts: 17 Sep, 2024

16 weeks$ 2,995
No Code AI and Machine Learning Specialization

Cohort Starts: 17 Sep, 2024

16 weeks$ 2,565
Post Graduate Program in Business Analysis

Cohort Starts: 19 Sep, 2024

6 Months$ 3,499
Post Graduate Program in Digital Marketing

Cohort Starts: 19 Sep, 2024

8 Months$ 3,000
Generative AI for Business Transformation

Cohort Starts: 20 Sep, 2024

16 weeks$ 2,995
Professional Certificate Program in Data Engineering

Cohort Starts: 23 Sep, 2024

32 weeks$ 3,850
Post Graduate Program in Data Analytics

Cohort Starts: 25 Sep, 2024

8 months$ 3,500

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Purdue Program Advisors

  • Jinsuh Lee

    Jinsuh Lee

    Clinical Assistant Professor of Management, Purdue University

    Jinsuh Lee teaches various marketing classes at Purdue. A Ph.D. in quantitative marketing, Lee puts the premium on the power of big data in marketing. He has developed data-driven marketing solutions such as loyalty and demand forecasting programs for top corporates like Samsung Electronics

    Twitter  LinkedIn
  • 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.

    Twitter  LinkedIn
  • Professor Sorin Adam Matei

    Professor Sorin Adam Matei

    Associate Dean of Research and Professor of Communication, Purdue University

    Prof. Matei researches digital knowledge creation and teaches various topics including human-AI/technology interaction, ethics, and strategies of AI and Data technologies. He leads many international research projects, including training & education in collaboration with Google News Lab.

    Twitter  LinkedIn
  • Ricardo Calix

    Ricardo Calix

    Associate Professor, Computer IT and Graphics

    Ricardo Calix is an Associate Professor of Computer Information Technology and Graphics at Purdue Northwest. He has a Ph.D. in Engineering Science from Louisiana State University in 2011. His research areas include ML, biometrics, intrusion detection systems, and NLP.

    Twitter  LinkedIn
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Purdue Learner's Reviews

  • Byron Bo Jones

    Byron Bo Jones

    Transformation Project Engineer

    I am thrilled to share that I have completed the Postgraduate Program in AI and ML Course from Simplilearn, in collaboration with IBM and Purdue University. I look forward to career advancement and participation in solving industry-aligned Artificial Intelligence and Machine Learning problems.

  • Rose Ashford

    Rose Ashford

    I had a great learning experience, and the faculty was very encouraging. The projects were vital in helping me understand whatever I learned during the course. I have also gained a lot of great professional contacts through this course. The course was very well structured, too.

  • Gordana Vujec

    Gordana Vujec

    Business Analyst

    Simplilearn has been a great pathfinder for me. It gave me great insight, knowledge, and guidelines about Business Analysis with a well-formulated course structure and interactive instructors. I was able to grab a new job after the course. So, I would highly recommend Simplilearn to everyone.

  • Merid Belayneh

    Merid Belayneh

    Postdoctoral Researcher

    I had a wonderful learning experience. The lectures were great and engaging. I am now looking forward to getting opportunities in the data science field.

  • Joseph (Zhiyu) Jiang

    Joseph (Zhiyu) Jiang

    I completed Simplilearn's Post-Graduate Program in Data Engineering, with Purdue University. I gained knowledge on critical topics like the Hadoop framework, Data Processing using Spark, Data Pipelines with Kafka, Big Data and more. The live sessions, industry projects, masterclasses, and IBM hackathons were very useful.

  • Marie Danielle Aissatou Bekolo

    Marie Danielle Aissatou Bekolo

    Staff Accountant

    I have enjoyed every session. My favorite was tableau and the capstone class with the tutor, Venkanna. Thank you, Simplilearn, for the fantastic job of helping professionals transform their careers. I feel more confident at work now than ever.

  • Olu Adeyinka MSc

    Olu Adeyinka MSc

    Senior Business System Analyst

    The faculty has excellent knowledge about the subject, and his ability to teach is very inspiring. The course content is comprehensive and updated.

  • Pegah Pourebrahim

    Pegah Pourebrahim

    Market Researcher

    I enjoyed the blended learning feature, which combines live classes with self-paced learning. The instructors were competent and engaging, and the course material was easy to follow and understand. The course included case studies from the actual world and hands-on tasks.

  • Cristian Hernández

    Cristian Hernández

    Strategic Sourcing, Procurement

    The instructor is highly knowledgeable and organized. His teaching methodology is commendable. The training sessions are great and informative.

  • Thomas McManus

    Thomas McManus

    Information Systems Engineer

    The instructor is exceptionally knowledgeable. Capstone nicely wraps up what we've been trained in the previous seven courses, and I feel more comfortable handling data analysis now. I look forward to bringing my newly obtained data scientist skillset to my job.

  • Caleb Navarro

    Caleb Navarro

    The trainer was highly skilled and took the time to answer every single question, and explained how to think of the BA framework from the right perspective. The sessions were very interactive and focused on content and explained each knowledge area in detail.

  • Magdalena Szarafin

    Magdalena Szarafin

    Manager Group Accounting & Data Analytics

    My decision to upskill myself in data science from Simplilearn was a great choice. After completing my course, I was assigned many new projects to work on in my desired field of Data Analytics.

  • Vy Tran

    Vy Tran

    I was keenly looking for a change in my domain from business consultancy to IT(Business Analytics). This Post Graduate Program in Business Analysis course helped me achieve the same. I am proficient in business analysis now and am looking for job profiles that suit my skill set.

  • Kevin García Oviedo

    Kevin García Oviedo

    GTM-E Project Manager

    I am happy to share that I completed my post-graduate program in Business Analytics offered by Simplilearn and Purdue University after seven months of dedicated learning. It was an incredibly insightful program with unique real-world projects.

  • A Anthony Davis

    A Anthony Davis

    Simplilearn has one of the best programs available online to earn real-world skills that are in demand worldwide. The Live classes had an industry expert as a lecturer, and you leave each session with a wealth of knowledge and practical skills that can advance your career. Thanks for an excellent experience!

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Industry Projects

  • Project 1

    Create a Virtual Assistant with Generative AI

    Develop a conversational chatbot that can engage in meaningful dialogues, answer questions, provide recommendations, and assist with tasks based on the documents provided.

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  • Project 2

    Develop an Ecommerce App with Python

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

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  • Project 3

    Build an Online Car Rental Platform

    Create an online car rental platform integrating scheduling and billing features and leveraging object-oriented programming techniques

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  • Project 4

    Utilize Time Forecasting to Forecast for the Food Industry

    Use data science techniques, such as time series forecasting, to help a data analytics company forecast demand for different restaurant items.

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  • Project 5

    Marketing Strategies with Exploratory Data Analysis

    Perform exploratory data analysis and hypothesis testing to better understand the various factors that contribute to customer acquisition.

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  • Project 6

    Use Cluster Analysis for Song Classification

    Perform cluster analysis to create a recommended playlist of songs for users based on their user behavior.

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  • Project 7

    Predicting Employee Iteration with Machine Learning

    Build a machine learning model that predicts a company's employee attrition rate by identifying patterns in their work habits and desire to stay with the company.

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  • Project 8

    Utilize Deep Learning to Automate Ship Detection

    Use deep learning concepts, such as CNN, to automate a system that detects and prevents faulty situations resulting from human error and identifies the type of ships

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  • Project 9

    Deep Learning models to Predict House Loan Repayment

    Create a model that predicts whether or not an applicant can repay a loan using historical data.

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  • Project 10

    Detecting Diabetics with CNN and Deploying with TensorFlow

    Use distributed training to construct a CNN model capable of detecting diabetic retinopathy and deploy it using TensorFlow Serving for an accurate diagnosis.

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  • Project 11

    Facial Recognition for Healthcare Systems with Deep learning

    Leverage deep learning algorithms to develop a facial recognition feature that helps diagnose patients for genetic disorders and their variations.

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  • Project 12

    Employee performance Mapping

    Utilize SQL databases to map employee performance and construct reports for appraisals

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  • Project 13

    Air Cargo Analysis with SQL

    Leverage SQL to generate reports using historical airline data, aiming to enhance services and improve customer experience.

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  • Project 14

    Ecommerce

    Develop a shopping app for an e-commerce company using Python.

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  • Project 15

    Food Service

    Use data science techniques, like time series forecasting, to help a data analytics company forecast demand for different restaurant items.

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  • Project 16

    Retail

    Use exploratory data analysis and statistical techniques to understand the factors contributing to a retail firm's customer acquisition.

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  • Project 17

    Production

    To understand their overall quality and sustainability, perform a feature analysis of water bottles using EDA and statistical techniques.

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  • Project 18

    Real Estate

    Use feature engineering to identify the top factors that influence price negotiations in the homebuying process.

    View Program
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