• Project 1: Predict Customer Churn with Clean Code
• Project 2: ML Pipeline for Short-term Rental Prices in NYC
• Project 3: Deploying a ML Model on Heroku with FastAPI
• Project 4: Dynamic Risk Assessment System

• 0. Intro to LLMOps
• 1. LLMOps in Practice
• 2. Case Studies & Advanced Topics
• 3. Future of LLMOps

• Project 1: Lidar Obstacle Detection Project
• Project 2: Camera Based 2D Feature Tracking
• Project 3: Track an Object in 3D Space
• Project 4: Radar Target Generation and Detection
• Project 5: Unscented Kalman Filter Highway Project

• 0. Introduction to AI Product in Business context
• 1. Creating A Dataset
• 2. Build A Model
• 3. Capstone: AI Product Business Proposal

• OxML aims to provide the participants with best-in-class training on a broad range of advanced topics and developments in machine learning (ML), including deep learning (DL). OxML schools by AI for Global Goals and in collaboration with CIFAR and the University of Oxford's Deep Medicine Program.
• ML Fundamentals consist of Statistical ML, Deep Learning, Optimisation, Mathematics of ML and related topics.
• ML x Health consists of Bayesian ML, Representation Learning, Geometric Deep Learning, Graph Neural Networks, Computer Vision, Knowledge Graphs, Knowledge-Aware ML, Symbolic Reasoning, Neuro-Symbolic AI and related topics.

• Grade: 92.65%
• Bayesian Networks, which rely on a directed graph; and Markov networks, which use an undirected graph.
• Theoretical properties of these representations and their use.
• Important extensions beyond the basic PGM representation, which allow more complex models to be encoded compactly.

Covers full stack of a vehicle’s autonomous capabilities in two terms along with projects.

Term 1: Computer Vision, Deep Learning, and Sensor Fusion

• Project 1: Finding Lane Lines
• Project 2: Advanced Lane Finding
• Project 3: Traffic Sign Classifier
• Project 4: Behavioral Cloning
• Project 5: Extended Kalman Filters

Term 2: Localization, Path Planning, Control, and System Integration

• Project 6: Kidnapped Vehicle
• Project 7: Highway Driving
• Project 8: PID Controller
• Project 9: System Integration

Data and Deployment Specialization, teaches how to apply the knowledge in various deployment scenarios and get introduced to TensorFlow Serving, TensorFlow, Hub, TensorBoard, implementing projects for adding to portfolio. It icludes the following courses:

• Browser-based Models with TensorFlow.js
• Device-based Models with TensorFlow Lite
• Data Pipelines with TensorFlow Data Services
• Advanced Deployment Scenarios with TensorFlow

The Deep Learning Specialization is a foundational program that helped you understanding the capabilities, challenges, and results of deep learning and prepared me to participate in the development of leading-edge AI technology, It icludes the following courses:

• Neural Networks and Deep Learning
• Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization
• Structuring Machine Learning Projects
• Convolutional Neural Networks
• Sequence Models

TensorFlow is one of the most in-demand and popular open-source deep learning frameworks available today. The DeepLearning.AI TensorFlow Developer Professional Certificate program teaches to apply machine learning skills with TensorFlow to enable building and training models. It icludes the following courses:

• Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning
• Convolutional Neural Networks in TensorFlow
• Natural Language Processing in TensorFlow
• Sequences, Time Series and Prediction

• Grade: 93.97%
• A broad introduction to machine learning, datamining, and statistical pattern recognition. Topics include: (i) Supervised learning (parametric/non-parametric algorithms, SVM, kernels, neural networks). (ii) Unsupervised learning (clustering, dimensionality reduction, recommender systems, deep learning). (iii) Best practices in machine learning (bias/variance theory; innovation process in machine learning and AI).
• Applying learning algorithms to building smart robots (perception, control), text understanding (web search, anti-spam), computer vision, medical informatics, audio, database mining, and other areas.

Given to Cyclists who has completed cycling route tours for all zones [ 1837KM ].

• Ara West Sea Lock to the lower basin of Nakdonggang (riv.)
• 4 Rivers route : Hangang (riv.), Geumgang (riv.), Nakdonggang (riv.), and Yeongsangang (riv.)
• Korean East Coast Trail cycling route
• Jeju Fantasy Bicycle Path

• Received Go green award for making an efficient solar vehicle with the team of 25 members for Asia’s largest solar vehicle competition, ESVC, Andhrapradesh, India, Mar 2017
• ISIEINDIA organized 8 Successful season of ESVC with consistency of improvement in Vehicle quality, innovations and dedication of teams. The Event (ESVC) is recognized solar car chain event by International Solar Car Federation in India. ESVC 3000+ is an authorized part of Electric Vehicle Mission 2030 by NITI AAYOG, Gov. of India.

• Won 2nd prize for the Robotics event of Path Finder (Line Follower) in the national level technical symposium VISION 2016 organized by Anna University, Chennai, Apr 2016
• We are expected to design and build a robot (Autonomous robot) with the given specifications in a Line follower competition. Points are assigned based on time to target, with deviations from the black line’s given path avoided. The robot will encounter various obstacles, zig-zag lines, curve lines, and intersecting lines, and it is expected to reach the target without being misled. We are also expected to program it in a different way in different rounds.