Teacher since July 2026
Felix Brandt
Numerical Python and code quality for data and AI projects that have outgrown a single notebook
9
tutors built
4.5Sample
average from 18 reviews
374Sample
lessons taught by their tutors
About Felix
I work on the part of AI projects nobody photographs: the arrays, dataframes, tests and packaging that let a prototype survive contact with real data. I came to this through scientific computing and later backend work, so I care about two things at once, getting the numbers right and keeping the code readable for the next person. My lessons are hands on. We take a small real task, write the obvious version, measure it, then improve it and explain why the improvement works. I am honest when a simpler tool or a plain loop is perfectly fine.
Knows about
Tutors by Felix
9 tutors
Profiling and Speeding Up Python
Find where your Python data and AI code really spends time and memory, then fix the parts that matter.78 lessonsSampleFelix Brandt$10pandas DataFrames for Everyday Analysispandas DataFrames for Everyday Analysis
Load, filter, group, join and summarise tabular data with pandas without the classic silent mistakes.71 lessonsSampleFelix Brandt$4Unit Tests for Python AI CodeUnit Tests for Python AI Code
Test the deterministic parts of LLM apps properly, with fake model clients instead of flaky live calls.61 lessonsSampleFelix Brandt$6Type Hints and Project StructureType Hints and Project Structure
Organise a growing AI codebase with clear modules, type hints and data models others can follow.52 lessonsSampleFelix Brandt$6Plotting Data with Python ChartsPlotting Data with Python Charts
Make clear, honest charts in Python, from quick looks at data to training curves you can trust.42 lessonsSampleFelix BrandtFreeAsync Python for Many API CallsAsync Python for Many API Calls
Run hundreds of model or web API calls concurrently with asyncio, limits, retries and clean results.41 lessonsSampleFelix Brandt$9NumPy Arrays from the Ground UpNumPy Arrays from the Ground Up
Think in arrays: shapes, axes, broadcasting and vectorised maths, with embeddings as the running example.29 lessonsSampleFelix Brandt$4Packaging and Sharing a Python ProjectPackaging and Sharing a Python Project
Turn your AI scripts into an installable package with clear dependencies, versions and a command line tool.Felix Brandt$7Handling Large Data Files in PythonHandling Large Data Files in Python
Work with datasets bigger than memory using chunks, smart dtypes, columnar formats and streaming.Felix Brandt$7Recent reviews
What students said about Felix's tutors.
- Bianca T.Sample
The habit of checking row counts after every merge caught a duplicate key problem in my real report on day two. validate is now in all my joins.
- Elif K.Sample
Clear on views versus copies, which had burned me before. Wanted a bit more on 3D arrays but the basics are very solid.
- Sebastian K.Sample
Replaced apply with map and a merge, from many minutes to seconds. The insistence on comparing outputs before and after caught one subtle change.
- Jonas W.Sample
Learned the subplots approach properly instead of copying snippets. The log scale tip for loss curves changed how I read my training runs.
- Arjun S.Sample
Writing shapes out by hand for broadcasting felt childish for a minute and then fixed every bug I had. The embedding similarity exercise tied it all together.
- Mei L.Sample
Practical examples with ticket data. The note about pandas behaviour changing between versions saved me from a confusing warning.