Master of Science in Artificial Intelligence & Machine Learning Ops

Highlights:

• In the Technical Training Participants will Gain In The Areas Of:

  • Core Artificial Intelligence Methods,
  • Computational Science, Electives That Incorporate Computer Vision,
  • Text Mining And Natural Language Processing,
  • Big Data And Robotics And Autonomous Systems And Reinforcement Learning.

• This Program Includes A Product Development Boot Camp To Solve Real Industry Problems Via Building Of Prototypes.

• Career Assistance During Product Development Boot Camp will help the Learners to build their future.

• Creating Cutting-edge Business Solutions, To Create Data Science Professionals This 2-year Master Of Science In Artificial Intelligence & Machine Learning Develops Is Designed.

• For Busy Professionals In A Flexible Online-blended Interactive Format, Works. The Program consists of A Rigorous Curriculum With Of 220+ Teaching Hours, Including 750+ Learning Hours & 212+ Lab Hours Offered In Total.

• A Master Dissertation At The End Of The Program Will Give Hands-on Experience along with On How To Use Complex Research-driven Data And Apply It To Solve your minor to major Business Problems.

Scholar Guided Master Dissertation

• Tools And Techniques Learnt During The Program By The Student To Gain Deep Technical Professional Experience By Applying The Concepts, Allows In Implementing, Artificial Intelligence Solutions And  Developing Machine Learning.
• A Master Dissertation Spread Across 20 Weeks Includes The Last Leg Of The Program.

• Under The Guidance Of An Assigned Scholar, The Research Using Data helps the Student To Draw Reasonable Recommendations, Validate Research Paper Results And The Dissertation Encourages Exhaustive Study.

Learning Outcomes

• In Algorithm Development And Visualization Learning Areas Tools Including R, Python & Tableau And Specialized Advanced Machine Get Competencies Such As NLP, Big Data, Robotics & Reinforcement Learning.

• To Obtain Hands-On Experience With Industry Prototype Building And Working, Application for Business And Data Thinking To Complex Research Problems plays a vital role.

• To Solve Complex Machine Learning Problems With Competencies In Data Mining, Regression Analysis, Text Mining, And Predictive Analysis make it Understandable.

• Understanding Business Problems To Analytical And Mathematical Problems, Data Understanding, Data Preparation, Modelling, Evaluation, And Deployment is the Entire AI Algorithm Development And Deployment Cycle Gain used to Confidence And Mastery.

• To Solve Big Data Problems Using Engines Like Apache Spark & Hadoop Ecosystem Analyze makes it less complex.

M.Sc. In Ml & AI, Ops Offers Industry Focused Curriculum With 8 Academic Terms. Each Course Is one After The Other And is Completed with In 15-20 Days Per Course.

Electives:

• Big Data: An Overview Of Big Data And Hadoop Ecosystems.
• Text Mining And NIP, Deep Learning For NIP.
• Robotics And Autonomous Systems And Reinforcement Learning.
• Computer Vision Fundamentals And Deep Learning Applications.

Quarter 1 – Mathematics & Computer Science Courses are

• • Foundations Of Probability And Statistics For Data Science

• Advanced Mathematical Analysis For Data Science

Quarter 2 – Computer Science And AI & Ml
Courses are

• Essential Engineering Skills In Big Data Analytics Using R And Python
• Statistics And Probability In Decision Modeling -1
• Statistics And Probability In Decision Modeling -2
• Advanced Data Structures And Algorithms

Quarter 3 – AI & Ml
Courses are

• Methods And Algorithms In Machine Learning -1
• Methods And Algorithms In Machine Learning -2

Quarter 4 – AI & Ml
Courses are

• Methods And Algorithms In Machine Learning -3
• AI And Decision Sciences
• Elective 1

Quarter 5 – AI & Ml And Business
Courses are

• Advanced Python Programming
• Elective 2
• Business Communication And Presentation Skills For Data Analytics
• Economics For Analysts
• Behavior Science And Analytics

Quarter 6 – Business Courses

• Business Law And Ethics
• Behavior Science And Analytics
• Digital And Social Media Analytics
• Product Management
• Project Management

Quarter 7 – Computer Science & Boot camp

• Architecting Enterprise Applications And Design Thinking-2
• Product Deployment Bootcamp
• Quantitative Research Methods
• Master Dissertation
• Project Management

Quarter 8 – Master Dissertation

• Master Dissertation

Students Will Focus On The Master Dissertation In The 2nd Half Of Q7 And The Entire Q8, Which Will Encourage Exhaustive Study And Require Students To Validate Research Paper Results And Prove Those Results Using The Guidance Of An Assigned Scholar.

The 24-month Program With 8 Academic Terms Equips You With The Most Coveted Skills Like:

Careers Roles As Applied Scientists, Data Scientists And Machine Learning Engineers Post Completion Of The Course Participants Can Advance Along With Data Driven Companies Like Amazon, Linked in, Google Among Many Others.

This Program Is For Learners Who Have Mid-level Experienced Professionals

Engineering (b Tech Degree) Or Graduation In Mathematics or computer Science/statistics/economics/b.Sc. Degree With Math Components With Minimum 50% Marks At Graduation Level And Minimum 2 Years Of Work Experience.

Or

 Engineering (m Tech Degree) Or For Learners Who Have Masters Degree In Mathematics or computer Science/statistics/economics/M.Sc. Degree With Math Components With Minimum 50% Marks At Graduation Level And Minimum 1 Years Of Work Experience.

Candidates May Have To Go Through An Online Interview Process.