Infosys Training Material ((link))

Here is some useful content related to "Infosys training material" , based on commonly available resources for Infosys’ onboarding and foundational programs (e.g., Campus Connect, Generic Training, Stream-specific tracks).


What does AI training material look like inside Infosys?

1. Learning Objectives

By the end of this module, the trainee will be able to: infosys training material


D. Abstraction

Definition: Abstraction means hiding complex implementation details and showing only the necessary features of the object. Here is some useful content related to "Infosys

Analogy: When you use an ATM machine, you see options like "Withdraw Cash" and "Check Balance." You do not see the backend database queries, network handshakes, or encryption algorithms happening behind the scenes. This is Abstraction. What does AI training material look like inside Infosys


Key Components of the Material

| Module Category | Examples | Format | |----------------|----------|--------| | Foundational | Generic SDLC, OOP concepts, DBMS, networking | PDFs, video lectures, interactive quizzes | | Technology Tracks | Java Full Stack, .NET, Python, DevOps, Cloud (AWS/Azure), RPA, Mainframes | Hands-on labs, guided projects, code repositories | | Soft Skills & Communication | Business email writing, presentation skills, client handling | Case studies, role-play scripts, e-learning modules | | Process & Compliance | ISO standards, Infosys IP policies, data privacy (GDPR), information security | SCORM-compliant courses, certification assessments | | Agile & Tools | Jira, Confluence, Git, Jenkins, Agile ceremonies | Simulated team workflows, step-by-step tool walkthroughs |

5. Assessment Pattern (The "Clearance" Criteria)

This is the most critical part. Training is high-pressure because failure means remediation or, in rare cases, exit from the company.

  1. Periodic Assessments (PA): These are mid-term tests.
  2. Comprehensive Assessments (CA): The final exam at the end of Generic and Stream training.
  3. Cut-off: You generally need a score of 60% to 70% (varies by batch) to pass.
  4. Hands-on Exam: You will be given a problem statement (e.g., "Create a library management system") and must code it within a set time.