Certificate Course in Applied Data Analytics | CC ADA

The aim of this Applied Data Analytics programme is to develop the important data analytics related skill sets for the learners. These skills are necessary for professional in the domain of Data. Its design offers hands-on training in the context of real applications in the data domain.

The learners have a freedom to choose their application domain (from Text Analytics or Image Analytics) and their applications as their area of study. It is designed for graduate students who are seeking a stronger foundation in data analytics.

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Key Information


  • Understand ethics related to Data Science and analytics.
  • Identify and apply various machine learning techniques for data analytics.
  • Learn a broad array of basic computational skills required for data analytics.

Learning Outcomes

At the successful completion of this program student will be able to

  • LO1: Implement solutions to data analysis problems using latest tools and technologies in their domain.
  • LO2: Discuss ethical practices related to data-driven decision-making.

Eligibility Criteria

  • Diploma or UG in Engineering and Technology (COMP/IT/ETRX/EXTC/Allied) OR B.Sc IT/COMP OR
  • Candidates studying in final year of Diploma Engineering and Technology (COMP/IT/ETRX/EXTC/Allied Branches) / B.Sc IT/COMP OR
  • Candidates studying in pre-final / final year of UG Engineering and Technology (COMP/IT/ETRX/EXTC/Allied)

List of Courses

  • Ethics for Data Science
  • Advanced Machine learning
  • Big Data and Real-time analytics
  • Elective :
    • Text Analytics and its applications
    • Image Analytics and its applications
  • Optimization Methods for Analytics
  • Computational_Lab_III / IV
  • Applied Project

Highlights & Mode of Study


  • Syllabus aligned to industry-recognized skills with emphasis on hands on training of the techniques and tools
  • Understanding the latest tools and technologies used in Industry
  • Foundation for career in the diverse\interdisciplinary fields
  • Flexible Schedule for working professionals

Mode of Study

  • Part Time
  • Online and / or Offline
  • 20 Hrs per week + Project
  • Flexibility in conduction of theory and laboratory courses