Data, AI, GenAI

Answer 118 multiple choice questions to check your Skill Calibration and to earn a Role Fit Badge.

Total Skills

118

READ CAREFULLY!! IMPORTANT INSTRUCTIONS FOR THE ASSESSMENT

General Assessment Instructions

This assessment is for Freshers intending to start career in Data, AI or GenAI streams in IT. This is a self assessment for them to reflect on their current competence in different technologies.

We encourage you to be utmost sincere and truthful while responding to the questions.

Honest responses will help you identify the roles for which you could be better prepared for and discover the skills where you need to further work on.

This is not a technical test, but a soft assessment of your understanding of different technologies. Please read the questions carefully and respond to them in utmost sincerity.

This profiling is likely to take about 10 minutes. Once you submit, you can view various role based reports. The report will comprise of capability index and suggested areas of improvement. Level rating (L1-L3) will be assessed at the skill group level only if threshold capability is achieved.
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# Skill Group Skills Description
1 Classification 8 Ability to apply classification algorithms and techniques to classify data
2 Clustering 6 Ability to apply clustering algorithms and techniques to identify and create clusters in the data
3 ML Techniques 9 Ability to apply different Machine Learning Techniques
4 NLP Algorithms 9 Ability to apply different Natural Language Processing Algorithms
5 Deep Learning 7 Understanding of Deep Learning technologies
6 AI Frameworks 9 Understanding of and ability to apply AI Frameworks and Tools
7 Programming 8 Comfort in using programming languages and tools meant primarily for AI and ML projects
8 ML Ops 5 Comfort in developing and using Machine Learning Ops pipeline
9 Data Science 6 Understanding of Data science and Data engineering aspects
10 Data Visualization 4 Ability to use data visualization tools and solutions to visualize data and understand trends
11 Data Techniques 5 Understanding of and ability to apply different Data Engineering techniques
12 Ethics & Governance 6 Appreciation of need for applying Ethics and Governance controls while building AI, GenAI solutions
13 Statistical Analysis 6 Understanding of statistical analysis techniques
14 GenAI API / Services 9 Understanding of various GenAI services and ability to use those in application development
15 GenAI Techniques 8 Understanding of and ability to apply various GenAI techniques like RAG, Langchain in the solution development
16 Front End 9 UI development technologies
17 API 4 They become the premise of inter component communication in modern softwares
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