Cohort-Based Data Science, ML & AI Engineering
Englishman Research runs live, cohort-based programs across data science, machine learning, and AI engineering — Python, scikit-learn, PyTorch, LLM engineering, and more. Built for absolute beginners and for GTM professionals who need to speak ML fluently. Competent instructors, projects, a cohort moving with you.
Case Study
Beacon Grid Partners, a mid-sized climate-tech company, had a five-person business development team closing enterprise deals for AI-driven grid analytics — but every discovery call stalled the moment a prospect’s engineer got technical. They needed the whole team fluent enough in ML to run a discovery call solo, in eight weeks, ahead of their Q3 renewal push.
We baselined each rep’s ML literacy in week one, ran the core Applied AI for Business Development track across weeks two through five — vocabulary, model literacy, ROI framing, vendor evaluation — then spent weeks six and seven on mock discovery calls reviewed live by instructors and the rest of the cohort. Week eight was the capstone: each rep ran a real discovery call, unassisted.
Also run for teams at climate-tech, healthtech, and fintech companies.
Applied AI for Business Development — taught in-house at Englishman Research
The Five Domains
Python, SQL, statistics, and the data-literacy skills that everything else in this curriculum assumes you already have — built for people starting at zero.
8 capabilities on staffFeature engineering, model evaluation, and a production-grade ML workflow — taught the way it's actually run on a team, not the way a tutorial simplifies it.
4 capabilities on staffNeural networks, transformers, and large language models — from first architecture to a fine-tuned model you built and shipped yourself.
3 capabilities on staffDocker, cloud infrastructure, and the monitoring pipeline that turns a notebook model into something a company can actually run in production.
3 capabilities on staffML literacy built for revenue conversations — scoping AI proposals, running technical discovery, and reading a vendor's roadmap correctly.
3 capabilities on staffThe Full Stack
Core Programming
The language every other tool in this curriculum assumes you already read comfortably — the foundation everything else is built on.
Data Manipulation
The standard toolkit for cleaning, reshaping, and analyzing tabular data in Python — deceptively simple until the data gets messy.
Database Querying
The query language behind almost every real dataset you'll ever be handed at a job — not the clean, single-table version most courses teach.
Statistical Reasoning
The math underneath every model decision you'll make later in the program — taught as a tool, not a semester of abstract theory.
Charting & Storytelling
Turning a table of numbers into a chart that actually answers the question someone asked, instead of the default your tool suggests.
Spreadsheet Analysis
Pivot tables, lookups, and structured analysis in the tool every non-technical stakeholder in your career will still open first.
Code Collaboration
The version-control system behind every real engineering team's workflow — and the single biggest giveaway of a self-taught background.
Notebook Environments
The interactive notebook environment where almost all real exploratory data science and model prototyping actually happens.
Classical Machine Learning
The standard library for classical machine learning — simple to call, easy to misuse without noticing.
Applied ML Craft
The unglamorous, judgment-heavy work of turning raw data into signal a model can actually use.
Gradient Boosting
The gradient-boosted tree libraries behind most winning tabular-data models in industry and competition alike.
Experiment Tracking
The experiment-tracking layer that turns a folder of untitled notebooks into a reproducible model-development process.
Deep Learning Framework
The dominant deep learning framework in research and industry, with a learning curve that punishes anyone who skips the fundamentals.
Pretrained Models
The library and model hub behind almost every modern transformer model — a shortcut that still assumes you know what's under the hood.
LangChain, Prompting & Fine-Tuning
Building real applications on top of large language models — retrieval, prompting, and fine-tuning, taught as one connected discipline.
Containerization
The containerization standard that makes a model's environment reproducible on any machine, including production.
Cloud Deployment
Deploying and serving a trained model on real cloud infrastructure — the step most courses stop just short of.
Production ML
The pipeline and monitoring layer that catches a model quietly getting worse after it ships, before a customer notices.
Applied Business AI
Scoping what an AI feature or proposal will actually cost, take, and deliver — the skill that sits between sales and engineering.
Stakeholder Reporting
The dashboard tools every BD and revenue conversation eventually runs through — easy to open, easy to mislead with by accident.
Technical Due Diligence
Reading a vendor's AI roadmap the way an engineer would, before it ends up as a line item in a contract you're accountable for.
How We Work
Tell us your starting point — total beginner or BDM with real deal context — and we place you in the right track and the next cohort start date.
You learn alongside a live group, twice a week, with an instructor who reads your code and your questions in real time — not a pre-recorded lecture.
Every track ends in a project built on a messy, real dataset, reviewed by instructors and the rest of your cohort — not graded by a script.
You present a capstone, get instructor sign-off, and leave with a portfolio piece and a program certificate you can actually explain in an interview.
Frequently Asked
No — not for the Foundations track. It's built for people starting at exactly zero. If you already know Python and basic statistics, we'll place you further along, typically straight into ML Engineering or Deep Learning & AI Systems, after a short assessment.
Four steps: you apply and we assess your starting point and place you in a track, you attend live cohort sessions twice a week, you build applied projects reviewed by instructors and your cohort, then you present a capstone and receive a certificate. See "How We Work" below.
Yes. Corporate cohorts run for teams of four or more — usually on the Applied AI for Business Development track, or a custom mix across tracks. We baseline the team's starting literacy and build the cohort schedule around your quarter, not a generic calendar.
Every session is recorded, and each cohort has a built-in catch-up week before project reviews. If you're consistently behind, your instructor flags it early and adjusts your project timeline rather than letting you fall off the cohort's pace silently.
Yes. Weekly instructor office hours are open to everyone, and each cohort is paired with a mentor for code and project review outside of live sessions.
Foundations and ML Engineering graduates typically move into data analyst and junior ML roles; Deep Learning & AI Systems graduates move into AI engineering; Applied AI for Business Development graduates stay in BD, sales engineering, and solutions roles — now able to run technical conversations themselves.
Englishman Research was founded by Akano Wisdom, who also co-founded Englishman Integrated Services. The education practice was spun out of that company and now operates as its own independent cohort-based education entity, with separate curriculum, instructors, and client engagements.
Our Story
Englishman Research began as the specialist-analysis capability inside Englishman Integrated Services (Englishman Integrated Services Ltd, RC 1795728), the operating company co-founded by Akano Wisdom. As that capability — GREET pathway modeling, ANSYS Fluent CFD, VASP DFT, and the rest of a 21-tool stack — grew past a side function into a full practice, it was spun out into its own entity.
Englishman Research now operates independently: its own licenses, its own HPC infrastructure, its own client relationships, and its own focus on academic and R&D analysis work. Englishman Integrated Services continues to operate as a separate business. The two organizations share a founder and an origin story, not an operating structure.
Disclosed here for transparency: ownership details reflect Akano Wisdom's current stake in Englishman Integrated Services, a separate company from Englishman Research.
Who We Work With
Free courses favor lighter, friendlier tooling and skip the parts that actually trip people up on the job — the messy dataset, the broken training run, the prospect who asks a hard technical question mid-call. That's an understandable trade-off for a free course. But it creates a gap: the moment you need to defend a model choice, scope a real proposal, or run a technical conversation solo, you need more than a tutorial gave you.
Englishman Research closes that gap. We keep the live instructors, the project review, and the cohort structure in-house so you don't have to build the discipline of finishing yourself.
Capabilities
A team of over 11 instructors and mentors teaches every tool in the curriculum live, from Python and SQL through PyTorch, LLM engineering, Docker, and AI product scoping. Every track ends in a project on a messy, real dataset, reviewed by instructors and your cohort.
Live Cohort Platform
What Clients Say
"I'd started three different online courses and never finished one. Having a live cohort and an actual deadline changed everything — I built my first real model in week four."
— Magnus Unuegbu, Foundations Track
"I used to freeze the second a prospect's engineer got technical. Eight weeks into the Applied AI for Business Development track, I was running discovery calls solo — and closing them."
— BD Lead, Eminence Drilling and Completion Services
"The project review sessions were the whole program for me. Getting a real instructor to read my code every two weeks did more than any tutorial ever did. Worth every penny."
— Anonymized Cohort Graduate, ML Engineering Track
Join a Cohort
Individual enrollment, a team cohort, or an ongoing corporate training partnership — tell us what you're trying to learn. Pick the path below that matches who you are, so it reaches the right desk immediately.
Teams & Companies
Send the brief below, or skip straight to a call on our calendar — whichever gets the conversation moving faster for you.
Or Book a Call on CalendlyIndividuals
Individual enrollment is handled on WhatsApp only — it's the fastest way to trade your background, find the right track, and lock in a cohort start date without losing the thread.
Chat on WhatsAppNo form, no email queue — WhatsApp is the required channel for individual enrollment.
