Aaryan Mittal

EDUCATION

Stanford University, USA

Technology Entrepreneurship: Completed a 4-credit course focusing on the fundamentals of launching and managing technology-based ventures.
Machine Learning: Completed a 3-credit course covering essential machine learning concepts, algorithms, and applications.
HPC-AI Summer Seminar Series: Participated in a 1-credit seminar series on High-Performance Computing and Artificial Intelligence, gaining insights into cutting-edge AI technologies and their applications.
CS 106A: Programming Methodology: Completed a 5-credit course on programming fundamentals using Java, emphasizing software engineering principles and problem-solving techniques.
Stats 216V: Introduction to Statistical Learning: Completed a course on the principles of statistical learning, covering key topics in regression, classification, and statistical modeling.

Completed 774 hours of intensive, hands-on coursework in software engineering, specializing in JavaScript and Python.
Achieved a position in the top 10% of the class, demonstrating strong technical skills and a deep understanding of software engineering concepts.
Recognized as the youngest participant in the cohort, showcasing exceptional talent and commitment to learning and growth in a highly competitive environment.

Structuring Machine Learning Projects: Completed a 20-hour course on best practices for structuring machine learning projects for maximum effectiveness.
Convolutional Neural Networks: Completed a 25-hour course covering CNN architectures and their applications in computer vision.
Neural Networks and Deep Learning: Completed a 25-hour course on foundational deep learning concepts, including neural networks and backpropagation.
Sequence Models: Completed a 25-hour course on sequence models, including Recurrent Neural Networks (RNNs), Long Short-Term Memory (LSTM), and their applications in natural language processing.
Improving Deep Neural Networks: Completed a 25-hour course on hyperparameter tuning, regularization techniques, and optimization strategies for deep learning models.

Supervised Machine Learning: Regression and Classification: Completed a 15-hour course on supervised learning techniques, including linear regression, logistic regression, and classification algorithms.
Advanced Learning Algorithms: Completed a 20-hour course covering advanced machine learning algorithms and their applications in various domains.
Unsupervised Learning, Recommenders, Reinforcement Learning: Completed a 15-hour course on unsupervised learning methods, recommendation systems, and reinforcement learning fundamentals.

IB Diploma: Studied the following subjects - Mathematics HL, Physics HL, Chemistry HL, Economics SL, English SL, Spanish SL.
IGCSE: Completed courses in English, Physics, Chemistry, Additional Mathematics, Computer Science, Business Management, Economics & Hindi.