*Attending weekly live lectures on topics under the AI umbrella, including data science, machine learning, deep learning, probability and statistics, led by Dr. Roland-Hassan Nasser.

*Developed Regression Models to predict rent in the NYC renting market, based on several features like apartment sq-ft, number of bedrooms, proximity to a train line, exact neighbourhood, and more.

*Worked primarily with tensorflow library, and keras framework. Also worked with libraries like sklearn, numpy, pandas, etc.

* Completed winter intensive introductory course on Quantum Computing

* Attended lectures, and completed labs on topics about Quantum Mechanics, Qubits, quantum gates and quantum measurement, quantum circuits, quantum algorithms and protocols, and applications of quantum computing.

* Explored uses, pros and cons of different types of Qubits including: Superconductors, Trapped Ions, Diamond NV Centres, Photonics.

* Attended lectures, and completed lab assignments on topics including quantum superposition, entanglement, and interference.

*Built virtual quantum circuits and simulations using quantumflytrap

*Learnt and used IBM's Qiskit to create quantum circuits performing tasks in the search problem space, and Quantum Key Distribution (QKD).

*Explored theoretical uses, computational complexities, as well as current implementations of Long-Term, and Near-Term quantum algorithms. Starting form the Deutsch-Josza algorithm, then Shor's algorithm, and what its super polynomial speedup could mean for cybersecurity, and blockchain technology. Studied Grover's search algorithm, and implemented it in Qiskit, observing quadratic speedups for search in unsorted lists.

*Explored Noisy Intermediate Scale Quantum Technology, and its benefits.