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MTech in AI

M. Tech in Artificial Intelligence

Duration : 2 years

Fee: 125000/- per year

Admission Link : https://xubpg.fdsbase.com/

Description:
The idea of Data Science/AI revolves around data driven Decision Making. Today, large amounts of data both structured and unstructured data is regenerated by industry which includes data from social media, sensors, e-commerce, among others. AI technologies, including deep learning and machine learning, are developing rapidly across the world, and are being applied to new use cases, affecting everything from business strategy to product design to operations.

The demand for trained and market ready skill sets in this field of data sciences and AI is growing exponentially. It is a challenge to get trained resources in the market and It requires a specialised and dedicated training (as this cannot be met by traditional teaching and learning process in an organisation).

M. Tech AI course provides deep drive skills in the principles and technologies that underlie AI including Machine Learning, Deep learning, NLP, Computer vision. This course offers an opportunity to learn the techniques, terminology and mathematics of deep learning, Machine learning, AI.

Curriculum Overview

  • The comprehensive curriculum offers a perfect blend of skills in Machine learning, Deep learning and NLP learning along with the business knowledge and a strategic perspective on the AI industry.
  • The main course work comprises of Experimental Learning and Practical application of the theoretical concepts on the domain application approach on real time projects.
  • The amalgamation of course modules and Capstone Project offers practical learning to the participants. The course is updated to provide students hands-on learning of the Machine Learning programs, deep learning.

Course Outline

  • Introduction to AI
  • Programming and Mathematics for Artificial Intelligence
  • Predictive modelling
  • Machine Learning
  • Deep Learning
  • Natural Language Processing (NLP)
  • Big Data Handling & Visualization
  • Introduction to Computer vision
  • Applications of AI
  • IoT

Key technology taught during the course

Basic & Advanced
Frameworks:		 NumPy, Pandas, Matplotlib
Dashboarding & Open
Machine
learning frameworks		 Jupyter, Plotly Dash & Streamlit
Web scraping Beautiful Soup, scrapy and Requests
Machine Leaning
framework		 Intel DAAL, Scikit-learn are key essential tools to build a successful ML
model.
NLP frameworks iNLTK, spacy, AllenNLP, are key essential tools to build a successful NLP
model.
Deep Learning &
Computer
Vision Frameworks		 TensorFlow 2.0, PyTorch & Open-CV to build video, image
analytics applications
Deployment Tools Plotly Dash & Streamlit simple and powerful frameworks for
productionize the code
OneAPI Intel Toolkit Intel Distribution of Python: NumPy, TBB4.py, Intel MKL, OpenVino,
Intel® VTune™ Profiler

Objective & Learning Outcomes:

By the end of this program, the participants will be able to:

  • Learn how to apply Modern Artificial Intelligence on different business verticals
  • Understand underneath mechanics of computer vision (CV), Speech Analytics & Natural Language Processing (NLP)
  • Learn & Build Deep Neural Networks Family of Algorithms and apply on AI concepts
  • Use state-of-the-art Object Detection Models, Image Segmentation
  • Use Emotion detection, Topics Modelling, Large scale language models & Chat bot
  • Build Application on real time problem statements using AI concepts
  • Implement AI systems to solve industrial, Business and social problems

Internship:

The Internship is an important component of the programme. It offers participants an opportunity to apply their overall course learning to solve real-world business problems. Each participant group is mentored by an industry mentor, to integrate theoretical and practical aspects.

Programme benefits to participants

  • Learning from subject-matter experts
  • Cutting-edge thought leadership
  • Relevant case studies from the industry
  • Built-in project work and Capstone projects as a part of the curriculum

Pedagogy

Experienced industry practitioners to interact with participants to share practical perspectives and insights into real business problems.

Certification

Industry Certification -> co-branded certificate

Eligibility for Admission

The eligibility for admission to M. Tech. in Artificial Intelligence shall be B.E./B.Tech(Computer Science/ Information Technology/ Electrical/ Electronics/Mechanical)/ M. Sc.(Computer Science/ Information Technology)/ MCA (with Physics and Mathematics/ Statistics at B. Sc. Level) with 60% marks in aggregate or equivalent.

Admission Procedure

  • Applicants are required to fill-up the application form, https://xubpg.fdsbase.com/. Upon successfully filling the online application form and paying the relevant application fee, the applicant will be intimated by email about the acceptance of the form.
  • The eligible candidates will be shortlisted based on academic credentials and/or extracurriculars and/or Admission test. The shortlisted candidates will be invited for Personal Interview leading to the final unified selection.

Start of the Program

The program will begin by the first week of December 2020 for the first year students. At this time the students will be given a Manual of Policies and Regulations which will be binding on them.