Other links:
Other links:
For someone who watched “Never Have I Ever”, might pick “Euphoria” as their next binge. For someone who watched “Euphoria”, might definitely pick “13 Reasons Why”. How is Netflix so definite about “Today’s Top Picks for You”? This pioneer in the streaming industry has mastered the art of gauging a customer’s sentiment – expressed in genres, actors, themes, ratings, viewing histories, social media following and other such categories of data. It has employed sentiment analysis and utilized advanced algorithms on its existing data to analyze each viewer’s sentiment towards specific content.
Embark on a transformative journey into the world of data science and learn the mechanics of how data is a building block game changer for all tech giants – from Amazon to Apple to Google. Applied Data Science with ML & AI is a hands-on live course that will enable you to build a solid foundation in data science and analysis techniques with various types of datasets such as tabular, textual, and images, that can be structured or unstructured. This course will teach you how to collect, analyze, apply suitable algorithms, inspect with visualization, build models and draw predictions to transform raw data into insights.
You will deep dive into both structured and unstructured data. In managing various types of data, you will learn new tools and techniques to analyze, visualize and present the key insights from data, enhancing your ability to communicate data-driven narratives. By the end of this course, you will have a well-rounded understanding of data science, ML/AI and practical skills, empowering you to tackle data-driven challenges.
You will kick off your data science journey with a hands-on capstone project. The project will engage you in thematic problem-solving with data. You will have three themes to choose from: data and economics, data and climate, data and healthcare and apply your learnings from each week to solve a problem under any of these themes or an intersection such as data science, machine learning, healthcare and climate change (e.g. Innovation Award Winner for The Vivli AMR Surveillance Open Data Re-Use Data Challenge)
What’s more? You will get an opportunity to contribute to projects ongoing at Ashoka University that are applying data science to solve real-world problems.
Unlock the power of data now and develop your skills for effective analysis and problem-solving!
Existing User? Log InThis course is for high schoolers looking to gain knowledge in data science, machine learning, artificial intelligence and develop data analytical skills or for those who are considering to study these subjects for higher education. It is for students aspiring to be data analysts, data scientists and anyone who is a data enthusiast.
Prerequisites: High proficiency in written & spoken English. You will be required to submit your latest mark sheet in the application form.
By the end of the programme, you will:
| Week | Lecture Module | Project Module |
|---|---|---|
| Week 1 | Decoding data science:
What, why, when & how? Gain foundational understanding of data sets and techniques for effective data analysis
|
Coding to decode data: Data types & attributes
Practice working with various data types and their attributes and set up a data science environment
|
| Week 2 | Going beyond data: Machine learning and artificial intelligence
Understand data as the building block for AI and ML and connect the dots to understand its applications
|
Practice algorithms: Deep learning and machine learning
Do hands-on practice on key algorithms, statistics and models
|
| Week 3 | Visualizing data: Creative coding & insights
Transform data into visual representation and insights to implement various types of data visualizations
|
Draw insights: Variety of visualizations
Play with various types of data to understand how to create and interpret a variety of data visualizations.
|
| Week 4 | Building prediction models: What, why, how?
Understand the steps in building a machine learning model and learn about different validation techniques
|
Deploy models: Real-world scenarios
Practice building a machine learning model and training pipeline and deploy models in real-world scenarios
|
| Week 5 | Counselling:
Get a chance to ask questions to the faculty and the mentor and get their answers and perspective. You are encouraged to ask questions to the faculty around the following aspects:
|
Mentoring:
You are encouraged to ask questions to the mentor around the following aspects:
|
You will choose from three themes: data and economics, data and climate, data and healthcare and solve a problem in your chosen theme using data. For your chosen theme and problem, you will analyze the three distinct types of datasets: tabular, textual, and image. By the end of the project, you will collate your learnings to present a solution to the identified problem within the chosen theme.
Rintu Kutum is a Faculty Fellow/Data Scientist at the Department of Computer Science, Ashoka University. He was the project coordinator (postdoctoral fellow) of “AL/ML for Healthcare” theme under the “City Knowledge Innovation Cluster – Delhi Research Implementation and Innovation” project at the Center for Excellence in Healthcare, IIIT-Delhi. His Ph.D. was in the area of Machine Learning, Genomics, and Gene regulatory Networks from CSIR-Institute of Genomics & Integrative Biology, New Delhi. He uses open source scientific computing languages such as R, Python, Julia etc., to accelerate his scientific research and promote via training. During his Ph.D. tenure, he has trained 22 scholars from various institutions across India. He has also been an eLife Ambassador during 2018-2019 and 2019-2020, and mainly worked on “Reproducibility research through Open Source Scientific Computing”. During this tenure, he organized 3 workshops with the help of various institutions; and has been actively working towards enhancing computer science literacy amongst life science scholars in India. He is one of the members, and instructor for Reproducibility for Everyone (R4E) Initiative. His long term interest is to train & nurture transdisciplinary scholars for doing collective research, and continues to work on the area of “Computational Health Sciences: Cellular Ecosystem to Public Health”.
All Ashoka Horizons courses offer a certificate on satisfactory completion of the programme.
Class participation will be assessed based on your active engagement in live sessions, contributions to discussion forums, and involvement in Teaching Fellow-led activities.
Achieve More…with Horizons:
*For select students, subject to discretion of the faculty
This programme is administered through an online platform. Students are expected to have a foundational understanding of computer usage, including but not limited to sending emails and conducting Internet searches. Consistent access to the Internet and a computer that aligns with the recommended minimum specifications are also requisite for participation in the programme.
Have a question about Ashoka Horizons Achievers Programme? Write to us on horizons@ashoka.edu.in
The project modules on the overall helped me gain more knowledge and ideas about the topic under study. Through the use of theoretical lenses, I understood the contexts for which the techniques used in data science are utilized. I liked the fact that it made the course more interactive and enjoyable and also helped me to further my understanding of the topic tackled and enhance my skills in solving problems.
The assignments are challenging and prompt us to think out of the box and figure out solutions to the given task. After attempting the assignments, I am met with a sense of accomplishment as I have learnt something new.
Prof Debayan Gupta
Assistant Professor of Computer Science, Ashoka University
PhD, Yale University
Schedule:May 17, 2025 (Saturday) – June 14, 2025 (Saturday)*
Prof Aalok Thakkar
Assistant Professor of Computer Science, Ashoka University
PhD, University of Pennsylvania
Schedule:May 17, 2025 (Saturday) – June 14, 2025 (Saturday)*
Parush Arora
Assistant Professor of Economics, Ashoka University
Ph.D. University of California, Irvine
Schedule:May 17, 2025 (Saturday) – June 14, 2025 (Saturday)*
