Pre-requisites:
Must have completed (Microcontroller Programming & Interfacing)
Programming Crash Course:
- Python:
- Basics
- Loops
- Blocks and Statements
- Lists
- Sets
- File I/O
- Modules and Functions
- OOPs concepts
- Keras:
- Introduction
- Installation and Configuration
- TensorFlow:
- Tensors
- TensorFlow Installation
- TensorFlow basics
Machine Learning:
- Introduction
- Supervised Machine Learning:
- Data gathering
- Data Cleaning
- Data Labeling
- Build ML models using Python
- Training and Testing the models
- Algorithms:
- Linear and Nonlinear classification
- Regression Techniques
- Decision Trees
- Oblique trees
- Random Forest
- Bayesian analysis and Naive Bayes classifier
- Algorithm Performance
- Unsupervised Machine Learning
- Text Classification using Python and NLTK / Naive Bayes
Deep Learning:
- Introduction to Neural Networks:
- Deep Neural Networks
- Perceptrons
- RNN, CNN, LSTM
- Deep Belief Network
- Semantic Hashing
- Building Deep Learning Models / Neural Networks using Keras and TensorFlow
- Testing and Training the models
- Convolutional Neural Networks
AI in Automobile Industry:
- Introduction
- Applications of AI in Automobile Industry:
- Computer Vision
- NLP
- Autonomous Driving
- Sensors
- Cameras
- Gathering and Processing Data from Devices / Sensors
- Vehicle Control Systems
- Decision Making
- Automatic Navigation
