Learning Path

Module 1

  • Analytical thinking and logical reasoning
  • Creative problem solving and innovation
  • Structured decision-making approaches
  • Understanding user needs and solution ideation
  • Iterative thinking and solution refinement

Module 2

  • Introduction to data-driven ecosystems
  • Applications of data science across domains
  • Understanding key data science terminologies
  • Types of data analysis and decision-making approaches
  • Foundational statistical and mathematical concepts
  • Overview of modern computing environments

Module 3

  • Programming fundamentals for data processing
  • Working with structured data formats
  • Data manipulation and transformation techniques
  • Handling data from multiple sources
  • Introduction to scalable data processing concepts

Module 4

  • Data exploration and pattern identification
  • Data cleaning and preprocessing approaches
  • Handling inconsistencies and anomalies
  • Visual representation of data insights
  • Communicating insights through dashboards and visuals

Module 5

  • Introduction to machine learning concepts
  • Predictive modelling and data-driven decision making
  • Classification and regression approaches
  • Clustering and pattern discovery techniques
  • Feature understanding and dimensionality concepts

Module 6

  • Fundamentals of cloud computing
  • Deployment and service models
  • Scalable data storage and processing concepts
  • Security and reliability considerations 
  • Emerging trends in cloud-based systems

Module 7

  • Application integration for data solutions
  • Model deployment concepts and workflows
  • Building end-to-end data applications
  • Model lifecycle and version management
  • Operationalising machine learning systems

Module 8

  • Problem identification and solution planning
  • Data collection and preparation workflows
  • Model development and evaluation approaches
  • Deployment and solution validation
  • Insight presentation and reporting

Tools Covered

Scholarship Test

The general aptitude test will cover the following topics:

  • Numerical Ability
  • Logical Reasoning
  • Verbal Ability
  • Data Manipulation

* The duration of the test will be 60 mins.

Elgibility

The program is open to the following candidates:

  • Engineering or science graduates, or those with a three-year diploma in any engineering branch, with foundational knowledge in Mathematics and Computer Fundamentals (equivalent to Plus Two).
  • Students who have completed their graduation but are awaiting final results may also apply.

* Please note, the ICT Academy of Kerala reserves the right to cancel the candidature if found ineligible at any point.

Highlights

  • Online and offline sessions tailored for graduates and professionals
  • Scholarships for meritorious candidates via ICTAK
  • 3 to 6 months of access to LinkedIn Learning / Unstop Premium
  • Comprehensive training in employability skills
  • 100% placement assistance for eligible candidates
  • Expert sessions by industry professionals

Our Alumni In Top Companies

Testimonial

Stories From
Our Learners

Discover how learners achieved their goals through our programs. These testimonials highlight the value and real-world outcomes we deliver.

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Candidate Testimonial – Mr. Sooraj S.

Candidate Testimonial – Ms. Krishna I.

Candidate Testimonial – Mr. Ajmal M. S.

Testimonial

Stories From
Our Learners

Discover how learners achieved their goals through our programs. These testimonials highlight the value and real-world outcomes we deliver.

View More

Candidate Testimonial – Ms. Indubala S.

Candidate Testimonial – Ms. Krishna I.

Candidate Testimonial – Ms. Indubala S.