Arya is working as a research and teaching fellow with Univ.AI.
She is currently working as a research fellow at the StellarDNN lab, IACS.
She is an incoming graduate student at Georgia Tech where she will specialize in machine learning.
Shibani Budhraja
A Psychologist and amateur musician exploring the world of Data Science.
Her current and future goals include working towards mastering Reinforcement Learning along with exploring ethics and biases in AI.
Her previous occupations have included a few hospital internships under neuropsychologists and psychiatrists , teaching at a NGO for young girls and thereafter teaching kids with special needs.
Vishnu M
Vishnu is the Program Coordinator for academic operations at Univ.AI.
He is a Computer Vision enthusiast and has recently completed his undergraduation from JECRC University, Jaipur.
Currently, he is also working as a research assistant in the StellarDNN lab at Harvard, where he is working on the intersection of Deep Learning and Astronomy.
Anshika Gupta
Anshika is the Co-ordinatior of Academic Development at Univ.AI.
She is a deep learning enthusiast and a recent undergraduate from JECRC University, Jaipur.
Previously, she was a Research Intern at Neos HealthTech where she worked on developing algorithms for medical image analysis and segmentation.
Lakshay Chawla
Lakshay is a CSE graduate from MAIT, Delhi.
Eventual goals include unravelling the mysteries of deep space with the help of ever-evolving AI.
You might find him engrossed in music and never-ending thoughts if not working for the future.
Hetansh Mehta
Hetansh Mehta is a Product Data Analyst at CollegeDunia web private limited.
He is proficient in leveraging Data Science and Analytics techniques to build products that people love to interact with.
In his free time, he likes to explore art galleries, museums, play chess and watch sports.
Chaitanya GVS
Chaitanya is currently interning at Movius Interactive, where he is actively engaged in Natural Language Processing and the development of Language Models.
He's a massive football fanatic with a keen interest in leveraging AI to revolutionize the game.
He spends his leisure time creating epic data visualizations on football, jamming to music, and binging on TV shows.
Nawang Bhutia
Nawang has completed his B.E in Information Science & Engineering from Acharya Institutes, Bangalore and currently working as a Teaching Assistant and Consultant in Univ.AI.
An avid learner who wants to learn more and explore the beautiful world of AI and it's application in various fields.
In his free time, he can be found supporting and analyzing games played by FC Barcelona.
Aamir Ansari
Aamir is currently a data scientist at Roadzen Technologies.
He is doing work in vision, audio and natural language modelling.
He is enthusiastic about football and the use cases of data science in it.
Mansi Palekar
Mansi recently graduated with flying colors from Somaiya Institute, Mumbai with a Master's in Mathematics and ready to take on the world!
She's always on the lookout for new challenges and opportunities to apply AI in recommendation systems and virtual assistants, making her a real tech-savvy brainiac.
When she's not busy solving mathematical equations or playing with AI, you can find her jamming out to music or getting her hands dirty in the garden!
Hemani Shah
Hemani is a machine learning enthusiast and a recent Computer Engineering undergraduate from GTU.
She worked as a data science intern at DeetsDigital.
She can be found reading novels in her free time.
Ibtisam Mohammad
Ibtisam has a Masters in Physics and is currently working on AI based Virtual Try-On at a startup.
Vrishbhanu Singh
Vrishbhanu Singh is a professional with a keen interest in Artificial Intelligence, particularly in the field of Reinforcement Learning.
He holds an undergraduate degree in Economics from Hindu College, Delhi University.
With his entrepreneurial spirit, he has established a startup in the construction industry and aims to incorporate AI to automate industrial plants.
In addition to his professional achievements, he is a former national-level cricketer and a talented musician who continues to play the guitar in his leisure time.
Aditya Doomra
Aditya is a research consultant with a hedge fund, previously he has worked in the data science team at BluSmart, where he worked on building traffic, demand, and supply prediction models.
He loves everything finance and data; and likes gaming and reading in his free time.
Ashwini Tayade
Ashwini, with a master's degree in Physics, excels as a freelance data scientist, leveraging data science for impactful insights.
Her passions lie in data privacy policies, healthcare AI, and applying design thinking methodologies.
During her leisure time, Ashwini finds joy in gaming, reading, and painting.
Ignacio Becker
Astronomer currently pursuing a Ph.D. in Computer Science at Pontificia Universidad Católica in Chile.
His main area of research is applied AI to astrophysical problems.
Nowadays, he focuses on developing models to process the real-time data of the next generation of telescopes.
Welcome to Python for Data Science.
The objective of this module is to provide fundamental understanding of the python programming language needed to follow an introductory course in Data Science.
You will start with the basics of python programming, including python data structures, functions and classes.
We follow this up by an introduction to Numerical Python (NumPy) and finally, the course will provide a basic introduction to linear regression from scratch.
Along the way, we will introduce foundational ideas of statistics, linear algebra and calculus.
At the end of this module, you will have the tools and the concepts needed to successfully undertake a rigorous course in machine learning.
This page introduces you to the team, the basic instructions, the schedule and various elements of our class.
The Team
Instructor
Dr. Ignacio Becker
Astronomer currently pursuing a Ph.D. in Computer Science at Pontificia Universidad Católica in Chile.
His main area of research is applied AI to astrophysical problems.
Nowadays, he focuses on developing models to process the real-time data of the next generation of telescopes.
Teaching Assistants
Click on avatars of the team members to know more about them.
The Coursework
We have very carefully designed the coursework to give you, the student, a wholesome learning experience.
We will hold two weekend sessions per week for a total of five weeks.
What to expect
Pre-Session
Before the session begins, students are expected to complete a pre-class reading assignment and attempt a quiz.
During Session
During the session, we will have live instruction interspaced with collaborative coding in small groups assisted by our teaching assistants. This will help you develop intuition for the core concepts and provide guidance on technical details.
Post-Session
After the session, students are expected to complete a short post-class quiz based on the principal concepts covered in class.
Course syllabus
The Class
Lecture Sessions:
Wednesday: 6:30 PM - 8:30 PM IST
Saturday: 6:30 PM - 8:30 PM IST
Office hours:
Monday: 6:30 PM - 7:30 PM IST
Please check your mail for more information.
Diversity & Inclusion
We actively seek and welcome people of diverse identities, from across the spectrum of disciplines and methods since Artificial Intelligence (AI) increasingly mediates our social, cultural, economic, and political interactions [1].
We believe in creating and maintaining an inclusive learning environment where all members feel safe, respected, and capable of producing their best work.
We commit to an experience for all participants that is free from – Harassment, bullying, and discrimination which includes but is not limited to:
Offensive comments related to age, race, religion, creed, color, gender (including transgender/gender identity/gender expression), sexual orientation, medical condition, physical or intellectual disability, pregnancy, or medical conditions, national origin or ancestry.
Intimidation, personal attacks, harassment, unnecessary disruption of talks during any of the learning activities.
Reference:
[1] K. Stathoulopoulos and J. C. Mateos-Garcia, “Gender Diversity in AI Research,” SSRN Electronic Journal, 2019 [Online]. Available: http://dx.doi.org/10.2139/ssrn.3428240.
Education software we use
Our lectures and labs are carried out via Zoom (install instructions).
Quizzes & exercises will be conducted on our own digital learning platform.
All exercises and homeworks in this course will be done in jupyter notebooks. This link will help you setup jupyter lab and get you acquianted with jupyter notebooks.
Parting Note
As you will learn in the course, programming for data science is not just about writing efficient code.
It requires proficiency in critical thinking, ideation & experimentation.
Keeping that in mind, you are advised to give your full active attention to every session.
We wish you well for the start of your data science journey.
