Live online instructor sessions (Direct to Device)
Deadline to Apply
16th August 2020
Rs.2,50,000/- + GST
Weekends (11:00 AM – 1:00 PM)
Course OverviewArtificial Intelligence (AI) and related technologies are revolutionising the way everyday world works. AI and Deep Learning (DL) are garnering a lot of attention of late because of some recent innovations – Alexa, Siri, humanoids and chatbots, to name a few. Given the increasing adoption of AI across industries, there is a growing demand for AI talent. In a LinkedIn report – 2020 Emerging Jobs Report India – featuring the top 15 emerging jobs, ‘AI Specialist’ stood at the number 2 position. Those aspiring to build a career in AI and DL can make a head-start with the Post Graduate Certificate in Artificial Intelligence & Deep Learning (PGCAIDL) program.
Module 1 - Emerging Technologies and Al
- Al in the context of emerging technologies
- Al applications
- History and evolution of Al
- Al in industry
- Future with Al
In this module, you will get introduced to Artificial Intelligence, its history, related terminologies and applications in industry. This will form the foundation for rest of your program.
Module 2 - Data is the New Oil
- What is Data Science?
- Who is a data scientist?
- What is Big Data?
- Tools and technologies
- Handling Text data
In this module, you will learn about foundations of Data Science. It is important that you are aware about the tools and technologies that are used for handling data.
Module 3 - Machine Learning
- What is Machine Learning?
- Supervised Learning: Regression and Classification
- Unsupervised Learning: Clustering
- Case studies/hands-on practice
In this module, you will learn about different machine learning algorithms and their applications. You will get hands-on practice with your very first predictions using machine learning models.
Module 4 - Programming with Tensorflow
- Tensorflow installation/Setup
- Tensorflow 1.0 programming concepts
- Computational Graphs & Sessions
- Tensorflow 2.0
Tensoflow is an end-to-end open source platform for machine learning. It provides advantages like easy model building, robust ML production and powerful experimentation. In this module, you will get hands-on experience of programming with Tensorflow.
Module 5 - Deep Learning and Neural Networks
- Introduction to Neural Networks
- Biological Neuron
- Perceptron structure
- Perceptron training
- Deep Neural Networks - Multilayer
- Keras API
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.
Module 6 - Image Recognition
- Computer vision and Open CV
- Convolutional Neural Networks
- Pretrained models
- Training a CNN model
- Image Classification
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.
Module 7 - Speech Recognition
- How speech recognition works?
- Natural Language Processing
- Recurrent Neural Networks - RNN
- Alexa Skills
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.
Module 8 - AI Applications
- Working of a self-driving car
- How drones work?
- What is Deep Fake?
Learn about cutting edge application of Artificial Intelligence from self-driving cars to drones in the sky.
Module 9 - Capstone Project*
- Classification of Chest X-rays
- Build a chat bot catering to customer service
End-to-end project to apply the concepts taught in the program.
* Candidates get to choose a project from a list of Capstone Projects. Problem statement and data set will be provided. Students will be provided a Capstone Project consisting of the following:
- Problem statement
- Data set
- Python based solution
- Mentoring sessions for the students for the Capstone Project
While experienced faculty will provide supervision for the projects and assignments, project completion will be the responsibility of the student.