Bootcamp — Weekly schedule

Week-by-week schedule of the AIRINA Labs Machine Learning & AI Bootcamp. Each week page lists live sessions, readings, lab notebooks, deliverables, and office hours.

This is the operational schedule for one full-time cohort (ten weeks). Part-time cohorts run the same content over twenty weeks at half the weekly load.

The dates below are filled in at intake; the schedule is otherwise stable across cohorts. Each week page is the single source of truth for what the cohort is doing that week — readings, recordings, lab links, deliverables — and replaces the inevitable email scramble.

For the program rationale, prerequisites, and ten-module curriculum overview, see the syllabus. For the final project, see the capstone brief.

| Week | Module | Title | Detail | |:---:|:---:|---|:---:| | 01 | M1 | **Python for data work** | [week 01](/workshops/ml-ai-bootcamp/en/week-01/) | | 02 | M2 | **Introduction to machine learning** | _(week 02 — coming)_ | | 03 | M3 | **Classical ML: regression, classification, clustering** | _(week 03 — coming)_ | | 04 | M4 | **Recommender systems** | _(week 04 — coming)_ | | 05 | M5 | **Natural language processing** | _(week 05 — coming)_ | | 06 | M6 | **Modern ML: ANN, CNN, RNN** | _(week 06 — coming)_ | | 07 | M7 | **Transformers and LLMs** | _(week 07 — coming)_ | | 08 | M8 | **Retrieval-augmented generation and agents** | _(week 08 — coming)_ | | 09 | M9 | **MLOps: from notebook to production** | _(week 09 — coming)_ | | 10 | M10 | **Capstone presentations** | _(week 10 — coming)_ |

How the week pages are structured

Every week page follows the same four-section layout, so cohort participants know exactly where to look:

  1. What you ship this week — the deliverable, due date, submission channel.
  2. Live sessions — date, time, topic, link, recording link (filled in after the session).
  3. Readings and prep — mandatory reading before each session, optional deepening reading.
  4. Lab notebooks — the hands-on work for the week, with notebook links and dataset URLs.

A short office hours block at the bottom of each week page lists the TA and the open Q&A slots.

Operational notes

  • Sessions run on Africa/Lagos time (UTC+1) by default; recordings and notebooks are timezone-agnostic. Part-time cohorts negotiate session times at intake.
  • Lab notebooks live in a public GitHub repo that mirrors this schedule. Each week’s lab is a tagged release.
  • The capstone milestones are interleaved with the regular modules: a proposal in week 4, a midterm review in week 7, a code freeze in week 9, the final presentations in week 10.

Looking for something specific?

  • Past recordings. Each week page lists the recording link once the session is complete. Recordings are retained for at least twelve months after the cohort.
  • Lab dataset access. Every lab notebook tells you where to download or generate the dataset. No dataset is gated.
  • Office hours. TA roster and slots are listed on the office hours page (filled in at intake).