Why Every AI Coding Assistant Needs a Memory Layer
A practical guide to context engineering for AI coding assistants, covering project rules, global preferences, implicit memory systems, and custom memory infrastructure.
Read the storyLearn about Python, Data, AI, R, Streamlit, and Apps.
From your first line of Python to your next AI app.
Learn with me through practical examples and real projects.
TUTORIAL EXAMPLE
Small experiments.
Useful discoveries.
Read a little code. Change something. See what happens. That's how we turn Python, data science, and AI into things you can build.
Find your next tutorialimport matplotlib.pyplot as plt # Plotting tools# Set the bar heights and their x-axis labels.scores = [72, 85, 95] # Change scoreslabels = ["A", "B", "C"] # Change bar label# Create a figure and its plotting area.fig, ax = plt.subplots()# Draw three bars with a solid teal fill.ax.bar(range(3), scores, width=0.52, color="#007c96", zorder=2)# Label the bars and fix the score scale at 0-100.ax.set_xticks(range(3), labels)ax.set(xlim=(-0.7, 2.7), ylim=(0, 100), yticks=[0, 50, 100])# Put horizontal grid lines behind the bars.ax.set_axisbelow(True)ax.grid(axis="y", alpha=0.2)# Mark the average with an orange dashed line.ax.axhline(sum(scores) / len(scores), color="#c56408", linestyle="--", zorder=3)# Print each score just above its bar.for index, score in enumerate(scores):ax.text(index, score + 3, str(score), ha="center")plt.show() # Display the finished chart
Change the code values. Updated lines are highlighted.
01 / BLOG
Articles & guides.
Things I've learned. Things you can build.
Explore all 134 articles
5 shown above. The remaining 129 are listed below by date, newest first. Undated entries appear last.
02 / VIDEO
Learn by doing.
Pull up a chair. Let's build something together.
Nifemi Aluko / October 01, 2026
The Data Professor: Stay in the Game Long Enough... That's Where Magic Happens
Chanin Nantasenamat on how a YouTube channel about data science became a pathway for millions of learners, and why staying in the game long enough is where the magic happens.
Watch on YouTube
PyCon US / September 18, 2026
The Ultimate Guide to Vibe Engineering with Streamlit
Vibe engineering restores what vibe coding skips: planning, review, testing, and deployment, with Streamlit and AI agents letting you work at the level of intent rather than syntax.
Watch on YouTube
Data Professor / April 19, 2026
How to gain AI / data experience even before graduation
How students can gain practical, job-ready experience in AI and data before graduation.
Watch on YouTubeExplore all 404 videos
3 shown above. The remaining 401 are listed below by date, newest first. Undated entries appear last.
03 / COURSES
Build something of your own.
Guided courses and playlists to learn at your own pace.
DEEPLEARNING.AI + SNOWFLAKE
Fast Prototyping of GenAI Apps with Streamlit
Learn to prototype generative AI apps with Streamlit in this hands-on course.
Explore the course
DATA PROFESSOR / YOUTUBE PLAYLIST
Streamlit (Web Application in Python)
Watch the playlist
DATA PROFESSOR / YOUTUBE PLAYLIST
Bioinformatics Project
Watch the playlist
DATA PROFESSOR / YOUTUBE PLAYLIST
Data Science 101
Watch the playlist04 / TALKS
Beyond the screen.
Conversations, workshops, and ideas shared in person.
Panel Talk / Nov 15, 2025
Symposia on AI in Dental Education
2nd Global Symposium on Artificial Intelligence in Dentistry
View talk
Technical Talk / Jan 12, 2023
Towards the Development of Bioinformatics Tools
The R User Group, Harvard Data Science Initiative
View talk
Plenary Talk / Nov 26, 2024
From DNA to UI: Connecting the Dots between Theory and Application in Bioinformatics
3rd Annual Meeting of Chilean Bioinformatics Society
View talkExplore all 20 talks
3 shown above. The remaining 17 are listed below by date, newest first. Undated entries appear last.
- From Lab Bench to Big Tech: How transferable skills bridged my research and tech careers
05 / RESEARCH
Rooted in research.
From bioinformatics to reproducible machine learning.
- Review articleTowards reproducible computational drug discovery
Explore all 167 publications
3 shown above. The remaining 164 are listed below by year, newest first.
- Review articleExploring the epigenetic drug discovery landscape
- Research articleThe MicroRNA interaction network of lipid diseases
- Research articlePepBio: Predicting the bioactivity of host defense peptides
- Book chapterTowards the revival of interpretable QSAR models
- Review articleComputer-Aided Drug Design of Bioactive Natural Products
- Research articleMaximizing computational tools for successful drug discovery
- Research articlePredicting Metabolic Syndrome using The Random Forest Method
- Book chapterElucidating the Structure-Activity Relationship of Curcumin and its Biological Activities
- Research articleExploring the chemical space of aromatase inhibitors
- Research articlePredicting antimicrobial activities of benzimidazole derivatives
- Research articleQSAR study of anti-prion activity of 2-aminothiazoles
- Research articlePyBact: An algorithm for bacterial identification
- Research articleMolecular docking of aromatase inhibitors
- Research articleData mining of magnetocardiograms for prediction of ischemic heart disease
- Research articleModeling the LPS neutralization activity of anti-endotoxins
- Research articleRoles of cysteine residue on chimeric green fluorescent protein: Implications on protein solubilization and fluorescent property
- Research articleComputational insights on sulfonamide imprinted polymers
06 / OPEN SOURCE
Building in the open.
A year of commits, issues, and pull requests across my personal and work accounts.
- GitHub followers
- 9,561 across both accounts
- Public repositories
- 345 across both accounts
- Contributions
- 1,766 in the last year
Public GitHub profiles and calendars, snapshot Oct 5, 2026. Private contributions appear only if an account shares them.
A COMMUNITY OF CURIOUS MINDS
Learning, together.
Media kit & audience demographics
Audience breakdown (2025). Figures are from the existing media kit, not live analytics.
Top geographies
India30.4%
United States12.8%
United Kingdom2.9%
Pakistan2.2%
Germany2.1%
Age distribution
18-24 years44.3%
25-34 years33.9%
35-44 years13.8%
45-54 years6%
55-64 years1.6%
65+ years0.3%
Gender distribution
Male76.9%
Female23%
THE PERSON BEHIND DATA PROFESSORRESEARCHER. EDUCATOR. BUILDER.
Hi, I'm Chanin.
Research taught me to ask questions.
Code lets me answer them.
I'm a Lead Developer Advocate for Open Source at Snowflake, creating educational content on building data apps with Streamlit and Snowflake. Before tech, I was a Professor of Bioinformatics, using Python to teach and perform research in computational drug discovery.
Since 2019, I've shared data science and AI tutorials on the Data Professor YouTube channel. Those videos have received more than 10 million views.