Request a Callback
Request a callback now! Fill in your details and one of our academic counselors will contact you promptly.
10 live projects + 1 capstone project
36+ hours of video content access
Weekly tasks and reports
Certificate of completion
OVERVIEW
Learn Artificial Intelligence today
Artificial Intelligence is a developing and highly sought-after domain to specialise in. Build the foundation, enhance your proficiency in its fundamental topics, and learn to make the smartest computer systems, equipped with AI.
NLP
Predictive Analysis
Artificial Neural Networks
Association Rules
Course Curriculum
Discover our comprehensive Artificial Intelligence course curriculum, designed to provide in-depth knowledge and practical skills
Introduction
- ML Fundamentals
- ML Common Use Cases
- Understanding Supervised and Unsupervised Learning Techniques
Clustering
- Similarity Metrics
- Distance Measure Types: Euclidean, Cosine Measures
- Creating predictive models
- Understanding K-Means Clustering
- Understanding TF-IDF, Cosine Similarity and their application to Vector Space Model
- Case study
Implementing Association Rule Mining
- What is Association Rules & its use cases?
- What is Recommendation Engine & it’s working?
- Recommendation Use-case
- Case study
Decision Tree Classifier
- How to build Decision trees
- What is Classification and its use cases?
- What is Decision Tree?
- Algorithm for Decision Tree Induction
- Creating a Decision Tree
- Confusion Matrix
- Case study
Random Forest Classifier
- What is Random Forests
- Features of Random Forest
- Out of Box Error Estimate and Variable Importance
- Case study
Support Vector Machines
- Case Study
- Introduction to SVMs
- SVM History
- Vectors Overview
- Decision Surfaces
- Linear SVMs
- The Kernel Trick
- Non-Linear SVMs
- The Kernel SVM
Feature Selection and Pre-processing
- How to select the right data
- Which are the best features to use
- Additional feature selection techniques
- A feature selection case study
- Preprocessing
- Preprocessing Scaling Techniques
- How to preprocess your data
- How to scale your data
- Feature Scaling Final Project
Introduction to Artificial Neural Networks
- The Detailed ANN
- The Activation Functions
- How do ANNs work & learn
- Gradient Descent
- Stochastic Gradient Descent
- Backpropogation
- Understand limitations of a Single Perceptron
- Understand Neural Networks in Detail
- Illustrate Multi-Layer Perceptron
- Backpropagation – Learning Algorithm
- Understand Backpropagation – Using Neural Network Example
- MLP Digit-Classifier using TensorFlow
- Building a multi-layered perceptron for classification
- Why Deep Networks
- Why Deep Networks give better accuracy?
- Use-Case Implementation
- Understand How Deep Network Works?
- How Backpropagation Works?
- Illustrate Forward pass, Backward pass
- Different variants of Gradient Descent
Meet our team of creative experts
Meet the talented and creative minds behind our work. Our mentors bring a wealth of experience and a passion for innovation to every mentorship course.
Ranjana Chawla
UI Designer
Ranjana Chawla
UI Designer
Ranjana Chawla
UI Designer
Teachnook Certificate
Upon successfully completing this course, you will receive a certificate of completion that helps potential employers assess your proficiency.
