Omar Tood is a data scientist, lead instructor, and researcher at Somast. He works across data engineering, machine learning, and AI applications, helping turn data into practical systems and products. His work includes building data pipelines, developing and integrating machine learning models, and supporting production-ready AI solutions. Alongside engineering, he leads technical training programs and contributes to research that advances Somast' work in artificial intelligence and data science.
Introduction to Data and Data Science
Data Analyst
Python Fundamentals
Data Analyst
Git & GitHub
Data Analyst
SQL for Data Analysis
Data Analyst
Excel for Data Analysis
Data Analyst
Statistics for Data Analysis
Data Analyst
Data Analysis with Pandas
Data Analyst
Data Cleaning & Data Processing
Data Analyst
Exploratory Data Analysis (EDA)
Data Analyst
Power BI
Data Analyst
Data Visualization & Storytelling
Data Analyst
Portfolio & Interview Preparation
Data Analyst
SomNLP-Corpus passes 1.1 billion tokens across 17 sources
17 upstream sources, 7.98M documents, 832M words and 1.136 billion subword tokens, measured over every document, plus what the four new sources changed and what the tokenizer still has to learn.
Sep 24, 2026 · 7 min
SomNLP-Corpus grows to 911M+ tokens across 13 sources
13 upstream sources, 7.35M documents, and ~912M subword tokens, plus a corrected, document-level tokenizer benchmark after we found and fixed a decode bug in v1.
Sep 1, 2026 · 6 min
Our Biggest Video Yet: What 12,000 Views in a Week Told Us About Somali Demand for AI Education
One week after we uploaded a 13-hour, fully Somali-language Data Science & Machine Learning course to YouTube, it passed 12,000 views, the biggest video and course we've published on the channel so far. It covers what the video was and what we're doing about what it told us.
Aug 8, 2026 · 6 min
We Gave a Frontier Model Somali Language Standards, and the Result Surprised Us
A demanding mathematics translation experiment revealed how the Somali Language Standard can help frontier models produce Somali that is more accurate, natural, consistent, and explainable.
Aug 7, 2026 · 11 min
Git & GitHub: The Bootcamp That Closes Every Gap the Last Four Left Behind
Our fifth program in this series, and the first not built around data science at all. Git & GitHub closes a gap every earlier cohort surfaced: people who could write working code but weren't yet confident collaborating on it the way professional teams and open source projects do.
Aug 7, 2026 · 6 min
Our Biggest Cohort Yet: Inside the June 2026 Data Science & Machine Learning Bootcamp
In June 2026 we ran our third Data Science & Machine Learning Bootcamp, and it's the biggest curriculum we've built for the program, eight core lessons on the full ML workflow, plus seven bonus sessions covering deep learning, generative AI, ethics, and career paths.
Jul 29, 2026 · 7 min
Python for Everyone: Teaching the Language Our Data Science Bootcamps Assumed You Already Knew
After two Data Science & Machine Learning cohorts, we kept seeing the same bottleneck: people excited about ML who got stuck on plain Python before they ever reached a model. Python for Everyone is the bootcamp we built to close that gap on its own.
Jul 6, 2026 · 6 min
SomNLP-Corpus: 793M+ tokens from six open sources
Our largest Somali text release yet: 1.67M clean documents, 529M words, and ~793M tokens from HPLT, CC100, mC4, OPUS, MADLAD, and MT560, filtered through a six-stage pipeline with deep cleaning.
Jun 9, 2026 · 5 min
Cohort Two: What We Changed for the Feb 2026 Data Science & Machine Learning Bootcamp
Five months after our first cohort, we ran a second Data Science & Machine Learning Bootcamp in February 2026. The core format held (one month, the same seven-stage ML workflow) but the curriculum itself changed in specific, deliberate ways.
Mar 26, 2026 · 6 min
Our First Bootcamp: How the Sep 2025 Data Science & Machine Learning Cohort Started It All
In September 2025 we ran our first Data Science & Machine Learning Bootcamp, a one-month, hands-on program built to take a complete beginner through the full ML workflow to a deployed project. It covers what we taught, why we built it, and what it set in motion.
Oct 26, 2025 · 6 min
