Artificial Intelligence and Machine Learning Education

Post Graduate Program in Artificial Intelligence & Machine Learning: Business Applications

The University of Texas at Austin – McCombs School of Business (2025)

Completed a 7-month intensive online program focused on applying AI and machine learning to real-world business challenges. The curriculum covered Python programming, machine learning, deep learning, natural language processing, computer vision, and generative AI. Engaged in hands-on projects using datasets from companies like Uber, Netflix, and Amazon, culminating in an industry-ready portfolio. Received mentorship from AI/ML experts and earned a certificate from UT Austin's McCombs School of Business.

Project Work

Apr 2025 | Course: Introduction to Natural Language Processing

Develop an an AI-driven sentiment analysis system that will automatically process and analyze news articles to gauge market sentiment, and summarize the news at a weekly level to enhance the accuracy of their stock price predictions and optimize investment strategies.

Skills & Tools Covered: Large Language Models, Transformers, Prompt Engineering, Exploratory Data Analysis, Data Manipulation, Word Embeddings, Text Preprocessing

Mar 2025 | Course: Introduction to Computer Vision

Build a robust image classifier using CNNs to efficiently classify different plant seedlings and weeds to improve crop yields and minimize human involvement

Skills & Tools Covered: Image Processing, Keras, Tensorflow, Convolutional Neural Networks, Transfer Learning

Feb 2025 | Course: Introduction to Neural Networks

Build a neural network using the data provided, to help the operations team identify the customers at high risk of churn. Provide recommendations on how to retain such customers.

Skills & Tools Covered: EDA, Data Preprocessing, TensorFlow, Keras, Artificial Neural Networks, Regularization

Jan 2025 | Course: Advanced Machine Learning

Create a predictive model using the data provided that can identify with high confidence, customers at risk of leaving the credit card services and the reason behind it. Provide recommendation on how the company can improve retention.

Skills & Tools Covered: EDA, RANDOM FOREST, Bagging, Boosting, SMOTE, Cross Validation, Data Pre-processing, Hyperparameter Tuning

Dec 2024 | Course: Machine Learning

Build a predictive model that identifies the customer attributes influencing loan acquisition. Provide business recommendations to help the bank improve their marketing efforts and conversion rates.

Skills & Tools Covered: EDA, Data Pre-processing, Model building - Decision Tree, Model Performance Evaluation and Improvement, Business Recommendations

Oct 2024 | Course: Introduction to Neural Networks

Perform exploratory data analysis to understand the demand of different restaurants and cuisines, and provide actionable insights for the company to enhance the customer experience and improve business.

Skills & Tools Covered: Python, Numpy, Pandas, Seaborn, Univariate and Bivariate Analysis, Exploratory Data Analysis, Business Recommendations

FoodHub: Data Mining

Product Management for AI & ML

Instructor: Jyothi Nookula (Netflix, ex-Meta, AWS, Etsy) – ELVTR (2023)

Completed a 6-week live online course designed to bridge the gap between traditional product management and AI/ML-driven innovation. Led by Jyothi Nookula, Director of Product Management for AI & ML at Netflix, the course emphasized translating business problems into AI solutions, understanding ML model lifecycles, and applying responsible AI principles. Key topics included data quality, feature engineering, generative AI, NLP, and multi-agent frameworks. The program culminated in a capstone project, where I developed an AI product proposal encompassing user research, risk assessment, and go-to-market strategy. Collaborated with a diverse cohort of professionals, enhancing cross-functional communication and strategic thinking in AI product development.