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Artificial Intelligence and Data Science: campus and exact course verification for IEM and UEM

Use a course-specific Artificial Intelligence and Data Science campus and exact course verification with dated official admission evidence, practical inspection tasks and clear campus limits.

Independent Akash Talks guidance. Official application, admission and fee decisions belong to the institution. How we verify information

Locate the exact programme

The engineering microsite lists AI and DS at New Town. Confirm that this is the location named in the current offer, and ask which department manages laboratories and projects. Do not transfer Salt Lake AIML eligibility or placement information into this programme merely because both titles contain artificial intelligence.

The dated Kolkata table includes AI and DS in the 60% X, 60% XII and PCM 45% group. Confirm the exact wording because CSE AI, AIML and Data Science appear under different labels and thresholds elsewhere. Ask for written mapping of any abbreviation on the application to the approved degree name.

Inspect the teaching environment

Map compulsory subjects into computing foundations, probability and statistics, data systems and AI methods. Check prerequisites and assessment hours rather than merely counting module names. Ask which topics are electives and which every student completes. A programme promising several fields should show how students practise them in connected projects without losing essential foundations.

Verify access through a practical task

Build a prediction workflow with a documented data collection process, a descriptive analysis, a baseline model and a held-out evaluation. Explain where a data-quality decision changes the model result. Present one useful failure case as well as the aggregate score. The project should connect statistical reasoning and software reproducibility rather than treating a notebook as a complete product.

Ask which shared compute and data resources serve the combined programme and whether access is reliable during project deadlines. Separate compulsory platform fees from optional external training. Budget for data storage and reproducible development before advanced paid tools. A resource list is useful only if undergraduates can actually use those resources for assessed work.

Read the offer as a record

For the Artificial Intelligence and Data Science offer, place the full institution name, university, programme title, entry route, batch and teaching address on one sheet. Compare them with the official course listing and fee document. Ask which office resolves discrepancies and keep the written answer. A group admission office may coordinate applications without being the place where every class or practical is held.

Record what the visit establishes

A Artificial Intelligence and Data Science campus visit can confirm what you observed and the questions staff answered on that date. It cannot establish access for a later batch, an unannounced specialisation or future placements. Record laboratory opening rules, individual assessment and travel between facilities. Use the observations to decide whether the environment supports the learning tasks you actually want to complete.

Official sources and verification

Sources checked on 26 October 2026. A source’s date, programme and campus limit which claims it supports. Official pages may change after review.

  1. UEM Kolkata — admissions and 2026 fee table

    Explicit 2026 batch fee and eligibility table. Lower undated blocks can conflict.

  2. IEM — official admissions information

    Displayed programme fee table; confirm the applicable campus, intake and batch.

  3. IEM Group — IEMJEE and IEMCET official examination notice

    Displayed 2026 examination cycle; historical dates, course routes and official admission contacts.

  4. IEM — engineering programmes and campus information

    Current engineering programme listings, campus allocation and affiliation wording.

Found a discrepancy? Send the page and the official notice for correction.

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