M. Sc. in Artificial Intelligence Ops (MSCAI)

Overview of the Program

  • The M. Sc. in Artificial Intelligence is a two year distance learning program designed to create Data Science professionals for creating cutting-edge business solutions
  • Transform into two roles, a data science and artificial intelligence researcher and product developer
  • Gain deep technical training in the areas of core artificial intelligence methods, algorithm building, simple end to end application deployment and courses that incorporate computer vision, text mining and natural language processing
  • Learn advanced programming, computation science , engineering and application architecture
  • Understand and solve complex machine learning problems
  • Deploy and Scale AI and ML applications
  • Specialize in advanced machine learning areas like computer vision, NLP and Quantum Computing

 

Specializations:

  • Deep Learning
  • DevOps

 

Learning Outcomes:

The learning outcomes for the students will be:

Deep Learning Specialization

  • Confidence and mastery in the entire AI algorithm development and basics of deployment cycle(understanding business problem to analytical and mathematical problem, data understanding, data preparation, modelling, evaluation and deployment)
  • Competency in algorithm development and visualization tools including R, Python and Tableau
  • Hands on experience with industry algorithm building and working to apply business and data thinking to complex research problems

 

DevOps Specialization

  • Confidence in the entire AI algorithm understanding and mastery in the deployment cycle
  • Strong computational and application architecture knowledge to deploy and scale AI and ML applications
  • Hands on experience with industry prototype building and working to apply business and data thinking to complex research problems

 

On Campus BootCamp

  • The student gets to attend an On Campus BootCamp for a hands-on immersive learning experience
  • BootCamp serves as an individual session post completion of a set of core AI and Elective courses and applying knowledge to solve real industry problems
  • The student will build and scale two applications/prototypes from start to finish individually using tools like Python, Docker and Git-hub

 

On Mentor Guided Masters Dissertation

  • The last leg of the program includes a Masters Dissertation spread across 20 weeks
  • The dissertation encourages exhaustive study & requires the student to validate research paper results and draw reasonable recommendations from the research using data, under the guidance of an assigned mentor
  • It allows the student to gain deep technical professional experience by applying the concepts, tools and techniques learnt during the program, in developing and implementing machine learning & artificial intelligence solutions

Structure of the Program (Duration: 2 years) -
Specialization Deep Learning

Structure of the Program (Duration: 2 years) -
Specialization DevOps

Sr. No. Subjects
1 Foundations of Probability and Statistics for Data Science
2 Digital and Social Media Analytics
3 Business Communication and Presentation Skills for Data Analytics
4 Essential Engineering Skills in Data Analytics using R and Python
Sr. No. Subjects
1 Statistics and Probability in Decision Modeling – 1
2 Statistics and Probability in Decision Modeling – 2
3 The Art and Science of Storytelling and Visualization
4 Hands-on Data Science Project 1
Sr. No. Subjects
1 Behavior Science and Analytics
2 Project Management
3 Methods and Algorithms in Machine Learning – 1
4 Design Thinking
Sr. No. Subjects
1 Methods and Algorithms in Machine Learning – 2
2 AI and Decision Science
3 Economics for Analysts
4 Hands-on Data Science Project 2
Sr. No. Subjects
1 Data Structures and Algorithms
2 Product Management
3 Business Law and Ethics
Sr. No. Subjects
1 Data Engineering – 1
2 Architecting Enterprise Applications
3 Quantitative Research Methods
4 Data Engineering – 2
Sr. No. Subjects
1 ML Algorithm Development Bootcamp
2 Masters Dissertation
Sr. No. Subjects
1 Master Dissertation

Eligibility Criteria

  • Mid-Level experienced professionals with preferably 2 yrs. of work experience
  • Engineering (B Tech degree) or graduation in Maths / Computer Science / Information Technology / Statistics / Economics / M. Sc. Degree with Math components with minimum 50% marks at graduation level

Fee Structure

The below mentioned Fee structure is subject to change at the discretion of the University. Any payment made via Demand Draft should be made in favour of “SVKM’s NMIMS” payable at Mumbai.
OPTION-1: INTEREST EMI FULL PAYMENT
  • Admission Processing Fees (One time, non-refundable): Rs. 1,500
  • Full Fee Payment Rs. 6,00,000
  • Full Fees Payment with 0% EMI Option
  • Processing Fee As Applicable
OPTION-2:FULL FEE PAYMENT
  • Admission Processing Fees (One time, non-refundable): Rs. 1,500
  • Program Fee per year Rs. 5,70,000
OPTION-3: ANNUAL FEE PAYMENT
  • Admission Processing Fees (One time, non-refundable): Rs. 1,500
  • Program Fee per year Rs. 3,00,000
  • Annual Payment Option – Easy 0%
  • EMI Options Available – No of Years 2
  • Processing Fee As Applicable

Additional Fee

In addition to the Fees, the following Fees are applicable:

  • An initial amount of Rs. 10,000/- from the program fee will be collected at the time of registration
  • EMI Facility (3, 6, 9, 12 months) available via credit cards of the following banks: HDFC Bank, ICICI Bank, Axis Bank, Citi Bank, Standard Chartered Bank, HSBC Bank, SBI, Kotak Mahindra Bank

 

Knowledge Partner and Career Assistance

 

  • Knowledge Partner: INSOFE
    • International School of Engineering (INSOFE) – one of Asia’s largest Data Science schools represents NGASCE as a knowledge partner to provide deep technical training in the field of artificial intelligence, data science & machine learning
    • INSOFE is the world’s leading research-driven educational institution in Applied Engineering with world-renowned faculty members holding PhDs from elite international universities and having worked as CXO’s in large analytics firms
    • It has routinely ranked amongst the top data science schools in the country and has academic affiliations with several high-ranking Indian and International Universities and several prominent institute-industry
    • In addition to training over 1000 students a year through its classroom program, INSOFE works with over 100 corporations globally to train CXO’s, mid-level managers and engineers
  • A dedicated team of NGASCE’s career advisors shall provide one-on-one support to students in CV development, arranging interviews and other areas of placement support
  • Get job opportunities from 500+ recruitment partners from NGASCE & INSOFE
  • Get access to the NGASCE Job Portal where you can apply to unlimited job positions

 

Qualifying Skills Required for Deep Learning Specialization

 

  • Math skills of linear algebra, calculus and coordinate geometry at college level are mandatory for the program
  • Programming skills like understanding of concepts like looping and iteration (such as while and for loops), branching (if-then-else constructs), functions and recursion and experience of writing simple programs that use these constructs are an added advantage

 

Qualifying Skills Required for Dev Ops Specialization

 

  • Programming background is mandatory with an understanding of concepts like looping and iteration (such as while and for loops), branching (if-then-else constructs), functions and recursion and experience of writing simple programs that use these constructs
  • Math skills of linear algebra, calculus and coordinate geometry at college level are an added advantage

 

Note

  • Qualifying test is applicable at the time of admission for those candidates who do not meet the eligibility criteria of their chosen specialisation
  • If the student wishes to change their specialization before Term 5, they need to meet qualifying criteria or appear qualifying test

Check the Features of the Programs in Video

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