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Program Features

Program Highlights

The program allows participants to:

  • 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.

 

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.

Scholar guided Master Dissertation

  • The last leg of the program includes a Master 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 scholar.
  • 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.

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.

Program Structure

The program has 8 academic terms including an industry-focused curriculum.

Specializations:

  • Deep Learning
  • DevOps

Tools & Skills

The 24-month program with 8 academic terms equips you with the most coveted skills like:

  • R
  • Tableau
  • Python
  • Hadoop
  • Apache Spark

Faculty

The faculty pool consists of over 50+ world class products builders, researchers and consultants scholars. These are practicing academicians & PhD holders from top Universities with 20+ years of average work experience, 75+ patents & 300+ research papers.

Career Options

Post completion of the course participants can advance their careers in roles as Applied Scientists, Data Scientists and Machine Learning Engineers with data driven companies like Amazon, LinkedIn, Google among many others.

Eligibility & Program Fee

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

NOTE:

  • Qualifying test is applicable to those who do not meet eligibility criteria of their chosen specialization. This has to be taken at the time of admission
  • Before start of TERM 5 student also has the provision to change the specialization provided they meet the eligibility criteria or clear the test

 

Eligibility Criteria for Deep Learning Specialization

  • Mid-Level experienced professionals with preferably 2 of work experience
  • Engineering (B Tech degree) or graduation in Maths/Computer Science/Statistics/Economics/M.Sc. Degree with Math components with minimum 50% marks at graduation level.
  • 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
  • For those who do not meet the above criteria, a test will be undertaken at the end of Year 1 in Math/Programming for entering the Specialization stream. It will be based on the following:
    • Math skills of linear algebra, calculus and coordinate geometry at college level AND/OR
    • 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.
  • Before start of TERM 5, if a student wishes to change the specialization, and does not meet the eligibility criteria he/she will be required to appear for a test. If student does not clear the assessment, he/she will be required to continue with the already chosen specialization.

 

Eligibility Criteria for Dev Ops Specialization

  • Mid-Level experienced professionals with preferably 2 yrs. of work experience
  • Engineering (B Tech degree) or graduation in Computer Science/Information Technology/Statistics/Economics/M.Sc. Degree with minimum 50% marks at graduation level.
  • Math skills of linear algebra, calculus and coordinate geometry at college level are an added advantage.
  • Programming background is mandatory with 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.
  • For those who do not meet the above criteria, a test will be undertaken at the time of admission. It will be based on the following:
    • 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 AND/OR
    • Math skills of linear algebra, calculus and coordinate geometry at college level.
  • Before start of TERM 5, if a student wishes to change the specialization, and does not meet the eligibility criteria he/she will be required to appear for a test. If student does not clear the assessment, he/she will be required to continue with the already chosen specialization.

 

  • Option 1:
    0% Interest EMI Fee Payment (in INR)

    6,00,000/-

    Full Fees Payment with 0% EMI Option.

    Processing Fee As Applicable.

  • Option 2:
    Full Fee Payment (in INR)

    5,70,000/-

    Full Fee Payment.

  • Option 3:
    Annual Fee Payment (in INR)

    3,00,000/-

    Annual Payment with Easy 0% EMI Options. (No of Years 2.)

    Processing Fee As Applicable.

  • An initial amount of Rs. 10,000/- from the program fee will be collected at the time of registration.
  • The above-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.
  • Admission Processing Fee : 1,500/-.
  • Now avail loan facility to pay fees for the Program even without a credit card.
  • 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.

Career Assistance

  • On Campus career assistance during product development bootcamp

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is setMaster of Science in Artificial Intelligence and Machine Learning Ops