AI
General
Mindset
Git Training & Markdown(Digital Documentation)
Understand basics of git, learn to use essential git commands & learn markdown documentation format :
- Overview of git (Diagram needed here with visuals of basic terminologies)
- Git commands : git clone, git config, git add, git status, git commit, git push, git pull, git branch, git checkout, and git merge
- Git Workflow
- Git Practice
- Assignment : Summarise Git learning in Markdown format.
Efficient Programming
Learn complex problem solving skills :
- Data Structures - Arrays, Linked List (SLL, DLL), Stack, Binary Search Tree, Hash Table, Dictionary
- Time Complexity, Space Complexity.
- Assignment : Solve a problem demonstrating above abilities : Peer review for best in class.
Skills
Intro Skills
Python Programming
Learn to implement python programming concepts :
- Datatypes : Containers, Lists, Dictionaries, Sets, Tuples, Functions, Classes
- Numpy: Arrays, Array indexing, datatypes, Array math, Broadcasting
- Jupiter Notebooks: Creating notebooks, Typical workflows
- Assignment : Exercises
Basic Skills
Machine Learning Basics
Understand basic machine learning algorithms :
- Types of ML Algorithms
- Random Forest Algorithm
- SVM
- KMeans
- KNN
- Naive Bayes
DNN Basics
Understand architecture and working principles of Deep Neural Network :
- DNN architecture
- Working Principles of DNN
- Forward Propogation
- Backward Propogation , Activation functions
- Important Terminologies : Epoch, Iteration, Batch_size, cost , learning rate , gradient descent.
Opencv Basics & Image Processing
Learn Basics of OpenCV and Image Processing :
- OpenCV - Basics
- OpenCV - Basics - Reading/Writing an Image
- OpenCV - Image Processing - Accessing Pixels, Transform Color Spaces
- OpenCV - Image Processing - Image Transforms
- OpenCV - Image Processing - Scaling and Cropping
- OpenCV - Image Processing - Filtering Images
- OpenCV - Image Processing - Histograms
Opencv Advanced Functions
Learn Advanced functions of OpenCV used for AI :
- OpenCV - Contour detection
- OpenCV - Thresholding
- OpenCV - Features detection, extraction and matching
- OpenCV - Object Detection
- OpenCV - Motion and Tracking
Advanced Skills
CNN Basics
Understand basic architecture and working principles of CNN :
- CNN Architecture
- Working Principles of CNN
- Introduction to CNN layers
CNN Advanced
Understand CNN layers in depth :
- Deep study of CNN layers
- Master a tool : A framework : To design CNN layers
- Building CNN architecture
Transfer Learning
Understand and implement transfer learning :
- What is transfer learning ?
- Freezing layers
- Determining layers to retrain
- Model training
Stanford Vision Course(CS231N)
Understanding convolutional neural network layers in depth :
- Architecture Overview
- ConvNet Layers :
Convolution layer
Pooling Layer
Normalization Layer
Fully-connected layer
Converting fully-connected layers to convolution layers - ConvNet Architecture :
Layer Patterns
Layer Sizing Patterns - Case Studies : (LeNet / AlexNet / ZFNet / GoogLeNet / VGGNet)
- Computational Considerations
Study of current best Models
Align student to understand industry ready products :
- Research paper study about chosen application
- Deep study top 3 methods to understand working principles
- Implementation
- Tuning of model using hyper-parameters
Tensorflow Basics
Understand Tensorflow basics :
- Tensors
- Tensor : types, rank, shape
- Constants, Variables, Placeholders, Graph, Session
- Creating Tensorflow Graph and Session
- Mathematical operations in tensorflow
- Eager Execution
- Practical : A Simple Tensorflow Program
Tensorflow Advanced (CNN)
Building a basic CNN model with tensorflow :
- Understanding CNN building APIs in tensorflow
- Building CNN model in tensorflow