IIT Guwahati Post Graduate Certificate Programme in Artificial Intelligence & Deep Learning

About Course

The IIT Guwahati Post Graduate Certificate Program in Artificial Intelligence & Deep Learning is an executive course that is designed for professionals looking to gain expertise in the field of Artificial Intelligence and Deep Learning. The program is designed to provide a comprehensive understanding of Artificial Intelligence and Deep Learning concepts, tools, and techniques.

The course is delivered through a combination of online and offline learning, making it accessible to professionals who are looking to upskill while balancing their work and personal commitments. The program is designed to be completed in 8 months and upon completion, participants will receive a Post Graduate Certificate from IIT Guwahati.

Develop a conceptual understanding of AI and be able to apply it to business problems
Gain a holistic view of the evolving AI tools and techniques and their applications
Learn concepts that include Programming with Python, Tensorflow, Machine Learning, Neural Networks, Deep Learning, etc.
Plan, design, deploy, and lead AI strategies effectively to enhance the efficiency of your organizational output

Course Content

Math and Statistics for AI (Self-paced)
This module will be a refresher for all the math and statistics concepts that will be required for the program going forward.

Probability
Statistics
Linear Algebra

Foundations of AI
In this module, you will get introduced to AI, its history, related terminologies and applications of artificial intelligence in industry. This will form the foundation for the rest of your program.

Programming with Python

Data Wrangling and Data Analysis
In this module, you will learn about foundations analysis of data using Python. It is important that you are aware about the tools and technologies that are used for handling data.

Supervised Machine Learning and Text Analytics
In this module, you will learn about different Supervised Machine Learning algorithms and their applications. You will get hands-on practice with your very first predictions using Supervised Machine Learning models.

Unsupervised Machine Learning
In this module, you will learn about different Unsupervised Machine Learning algorithms and their applications.

Hackathon 1

Programming with Tensorflow
Tensorflow is by far the most popular deep learning library and is extensively used in the industry . It is developed and open sourced by Google. This module provides extensive hands on learning on Tensorflow.Tensorflow is by far the most popular deep learning library and is extensively used in the industry. It is developed and open sourced by Google. This module provides extensive hands-on learning on Tensorflow.

Neural Networks and Deep Learning
Get introduced to the concept of a neuron and how multiple neurons can be used to construct an Artificial Neural Network. Deep Learning is a class of Machine Learning algorithms that progressively extract features for better understanding of the problem. You will learn about various Deep Learning models built using Artificial Neural Networks.

Computer Vision and Image Recognition
One of the popular applications of Deep Learning is in image recognition. You will learn how to build complex image recognition and object detection models and apply them to solve business use cases.

Natural Language Processing & Speech Recognition
Processing the naturally spoken language is one of the complex tasks faced by researchers. In this module, you will learn about Natural Language Processing and how Deep Learning models can be used to build speech recognition applications.

Advanced AI Applications
Learn about cutting-edge application of Artificial Intelligence from self-driving cars to drones in the sky.

Cloud Deployment of ML Models (Self-paced)
In this module you will learn about deploying the machine learning / deep learning modules using REST APIs on cloud.

Campus Immersion and Hackathon 2

Capstone Project

Fraud Analysis Using ML Algorithms
Enabling Business Intelligence for a Restaurant Aggregator
Land use classification based on satellite imagery
Retail customer segmentation
Telecom Customer Churn
Data Quality and Data Exploration of Credit card dataset
Chatbot using DialogFlow
Lung cancer Detection
Bone Age using X-Ray Images
.Prediction of Covid-19 spread using Time series with LSTM
Covid Vaccination Helpline- Customized chatbot using alexa blueprint

About Course

What Will You Learn?

Course Content

Math and Statistics for AI (Self-paced) This module will be a refresher for all the math and statistics concepts that will be required for the program going forward.

Probability

Statistics

Linear Algebra

Foundations of AI In this module, you will get introduced to AI, its history, related terminologies and applications of artificial intelligence in industry. This will form the foundation for the rest of your program.

AI in the context of emerging technologies

AI applications

History and evolution of AI

AI in industry

Future with AI

Programming with Python

Getting Started with Python

Linear Algebra with NumPy

Handling structured data using Pandas

Data Visualization using Python

Data Wrangling and Data Analysis In this module, you will learn about foundations analysis of data using Python. It is important that you are aware about the tools and technologies that are used for handling data.

Data Pre-Processing

Exploratory Data Analysis

Data Visualization

Supervised Machine Learning and Text Analytics In this module, you will learn about different Supervised Machine Learning algorithms and their applications. You will get hands-on practice with your very first predictions using Supervised Machine Learning models.

Linear Regression

kNN

Logistic Regression

Decision Trees

SVM

Ensembling / Random Forests

Optimization

Unsupervised Machine Learning In this module, you will learn about different Unsupervised Machine Learning algorithms and their applications.

Hierarchical Clustering

Agglomorative Clustering

kMeans Clustering

Hackathon 1

Tensorflow installation/setup

Tensorflow programming concepts

Computational graphs and sessions

Introduction to Neural Networks

Concept of perceptron

Back propogation

Deep Neural Networks – multilayer

Computer Vision and Image Recognition One of the popular applications of Deep Learning is in image recognition. You will learn how to build complex image recognition and object detection models and apply them to solve business use cases.

Computer vision and Open CV

Convolutional Neural Networks – CNN

Using pretrained models

Image classification- Binary and Multiclass

Object detection

Natural Language Processing & Speech Recognition Processing the naturally spoken language is one of the complex tasks faced by researchers. In this module, you will learn about Natural Language Processing and how Deep Learning models can be used to build speech recognition applications.

How speech recognition works?

Natural Language Processing

Recurrent Neural Networks – RNN

Chatbots

Alexa skills

Transformers

Advanced AI Applications Learn about cutting-edge application of Artificial Intelligence from self-driving cars to drones in the sky.

Drone Principle

Visual, Audio-Visual Deepfake and its future

Other AI Application

Cloud Deployment of ML Models (Self-paced) In this module you will learn about deploying the machine learning / deep learning modules using REST APIs on cloud.

Creating data pipelines

Writing production grade code

Creating REST APIs

Deploying APIs on cloud

Campus Immersion and Hackathon 2

Capstone Project

Fraud Analysis Using ML Algorithms

Enabling Business Intelligence for a Restaurant Aggregator

Land use classification based on satellite imagery

Retail customer segmentation

Telecom Customer Churn

Data Quality and Data Exploration of Credit card dataset

Chatbot using DialogFlow

Lung cancer Detection

Bone Age using X-Ray Images

.Prediction of Covid-19 spread using Time series with LSTM

Covid Vaccination Helpline- Customized chatbot using alexa blueprint