Field Notes Daily
Field Notes Daily
AI fundamentals — expert-led masterclasses, worldwide access
Masterclass · Artificial Intelligence

AI Fundamentals for Practical Work

  • Covers neural networks, language models, and decision systems without assuming a math background
  • Hands-on exercises using real tools — Python notebooks, open-source models, and API-based workflows
  • Structured for professionals who need working knowledge, not just theory
view schedule
Instructor demonstrating AI model behaviour during a Field Notes Daily masterclass session

What the programme covers

Eight modules move from foundational concepts to applied technique. Each session is self-contained enough to revisit, but structured so the sequence builds on itself.

8 modules
24h total content
268 enrolled
4.2 avg. rating
Module 01

How machine learning actually works

Pattern recognition, training loops, and the difference between supervised and unsupervised approaches — explained through concrete examples rather than equations.

3 hr 10 min
Module 02

Neural networks from input to output

Layers, weights, and activation functions. You build a small network by hand in a notebook to see exactly what each step does before touching a library.

2 hr 45 min
Module 03

Language models and how text gets processed

Tokenisation, embeddings, attention mechanisms. Covers GPT-style architectures at the level needed to use them responsibly and configure them for specific tasks.

3 hr 20 min
Module 04

Working with APIs and open-source models

Practical integration using REST APIs, Hugging Face pipelines, and local inference. Includes rate limits, cost estimation, and output validation patterns.

2 hr 55 min
Module 05

Decision systems and classification tasks

When to use a classifier versus a generative model. Evaluation metrics — precision, recall, F1 — explained through a worked dataset rather than abstract formulas.

2 hr 30 min
Module 06–08

Applied projects and review

Three guided projects covering text classification, image recognition basics, and a retrieval-augmented generation pipeline. Each includes a written debrief on what went wrong and why.

9 hr 20 min
6 live Q&A sessions
3 guided projects
12 notebook files
lifetime access

Taught by Adrienne Voclain

Adrienne spent eight years building production ML systems at two mid-size software companies before moving into education full-time in 2021. Her work focused on NLP pipelines and recommendation engines — the kind of applied problems that rarely match textbook examples.

She teaches from documented failure as much as from success. Each module includes notes on what broke during her own implementations and how those problems were diagnosed.

Background: Production ML engineering, NLP, applied data systems
Language: English — all materials, recordings, and Q&A sessions
Format: Pre-recorded video with live monthly review sessions
Prerequisites: Basic Python familiarity — no calculus or statistics required
4.2 · 268 reviews

Enrolment options

CA$349
one-time payment — no subscription
  • All 8 modules with full video recordings
  • 12 Python notebooks with working code
  • Access to 6 live Q&A sessions per year
  • 3 guided project briefs with instructor feedback
  • Certificate of completion from Field Notes Daily
  • Lifetime access including future content updates
enrol now

Group pricing is available for teams of 4 or more. Contact info@fieldnotesdaily.eu for details. Invoicing available for institutional purchases.