You will get Hands-on Generative AI & LLM training from a practicing AI engineering CEO
Project details
Hands-on AI/ML and LLM training from the CEO of a 15-person AI engineering firm who builds production AI systems daily. Yale Physics grad, former Head of Client Analytics in fixed income quant strategy at Morgan Stanley, Tiger Global derivatives trader. Nearly 20 years of teaching experience. This isn't pre-recorded lectures or toy datasets — it's applied, code-driven learning built around your real use cases.
Every session is 2 hours of focused, hands-on instruction. Covers the full AI/ML stack depending on your level: classical ML, NLP, large language models, prompt engineering, RAG, AI agents, fine-tuning, vector databases, LangChain, MLOps, and production deployment. Python, PyTorch, TensorFlow, scikit-learn, and the modern LLM toolchain.
Built for professionals upskilling into AI/ML, career pivoters targeting ML/AI roles, engineers integrating LLMs into products, and teams needing AI training. Starter ($750, 1 session, 2 hrs) for a specific topic or tool. Standard ($2750, 8 hrs) for structured training over several weeks. Advanced (5000, 8 sessions + async, 16 hrs) for full immersion with code review, a capstone project, and between-session mentorship.
Every session is 2 hours of focused, hands-on instruction. Covers the full AI/ML stack depending on your level: classical ML, NLP, large language models, prompt engineering, RAG, AI agents, fine-tuning, vector databases, LangChain, MLOps, and production deployment. Python, PyTorch, TensorFlow, scikit-learn, and the modern LLM toolchain.
Built for professionals upskilling into AI/ML, career pivoters targeting ML/AI roles, engineers integrating LLMs into products, and teams needing AI training. Starter ($750, 1 session, 2 hrs) for a specific topic or tool. Standard ($2750, 8 hrs) for structured training over several weeks. Advanced (5000, 8 sessions + async, 16 hrs) for full immersion with code review, a capstone project, and between-session mentorship.
AI Algorithms
Large Language Model, Multimodal Large Language Model, Regression Analysis, Transformer ModelAI Applications
AI Chatbot, AI Content Creation, AI-Enhanced Classification, AI-Generated Art, AI-Generated Code, Anomaly Detection, Conversational AI, Natural Language Generation, Natural Language Understanding, Sentiment Analysis, Time Series Analysis, Time Series ForecastingAI Development Language
PythonAI Tools
Azure OpenAI, Gradio, Hugging Face, Microsoft 365 Copilot, PyTorch, Streamlit, TensorFlowAI Models
BERT, ChatGPT, GPT-3, GPT-4, LLaMA, OpenAI Codex, WhisperWhat's included
| Service Tiers |
Starter
$750
|
Standard
$2,750
|
Advanced
$5,000
|
|---|---|---|---|
| Delivery Time | 1 day | 4 days | 8 days |
Number of Revisions | 0 | 0 | 0 |
AI Model Integration | - | - | - |
Batch Normalization | - | - | - |
Database Integration | - | - | - |
Detailed Code Comments | - | - | - |
Image Upscaling | - | - | - |
MLOps | - | - | - |
Model Deployment | - | - | - |
Model Documentation | - | - | - |
Model Monitoring | - | - | - |
Model Testing & Optimization | - | - | - |
Model Tuning | - | - | - |
Natural Language Processing | - | - | - |
NLP Tokenization | - | - | - |
Pre-Training | - | - | - |
Prompt Engineering | - | - | - |
Setup File | - | - | - |
Source Code | - | - | - |
Optional add-ons
You can add these on the next page.
additional sessions/review/content requests
(+ 1 Day)
+$375Frequently asked questions
About Clarence
AI/ML Engineering | Career Coach/Educator | Data Science | Tutor
Queens County, United States - 8:22 am local time
Today, I’m the CEO of AcceLLM, where I lead a team of 15 senior AI engineers building production-grade AI systems for companies that want measurable business outcomes — not another strategy PDF. Our work spans LLM-powered automation, multi-agent RAG systems, fine-tuning pipelines, and AI infrastructure designed to scale. I focus on bridging the gap between cutting-edge AI research and practical business execution, ensuring teams can move from experimentation to measurable ROI.
I also run Clarence Stephen Solutions, coaching professionals through career transitions into AI, data science, and quantitative fields. Mentorship is not a side note in my career — it’s part of the operating system that drives how I lead teams, how I structure learning, and how I deliver value to clients.
The path here has been diverse but connected. I started on the equity derivatives desk at Morgan Stanley, then traded FX and equity derivatives strategies at Tiger Global, before returning to Morgan Stanley to lead client analytics for fixed income quant strategy. From there, I transitioned into senior data science and AI roles across e-commerce, retail, and pet tech, including building Readify, a generative AI ed-tech startup inspired by my daughters’ love of reading. Across all these roles, the constant has been the same instinct: find the signal in the noise, build something that works, and make it understandable and actionable for both technical and non-technical audiences.
In AI, this translates to designing autonomous agent workflows, RAG pipelines, and ML-powered decision systems that handle complex business problems while remaining reliable, interpretable, and scalable. I’ve worked with LangChain, LlamaIndex, AutoGen, and LoRA fine-tuning, integrating LLMs with internal and external systems, implementing secure access, and designing systems that allow humans and AI to collaborate seamlessly.
Teaching Is How I Lead
Mentoring and teaching for over 20 years isn’t a footnote — it’s central to how I operate. I tutor professionals and students 1-on-1 in Python, SQL, machine learning, statistics, deep learning, data engineering, and AI fundamentals. I also cover the quantitative and finance foundations underpinning data science — probability, linear algebra, calculus, derivatives pricing, risk management, and trading strategies. Whether preparing for licensing exams like the Series 7 or standardized tests like the SAT, my approach is the same: teach deeply, contextualize practically, and make the material click.
Every session is customized. No canned curriculum. I meet learners where they are: career switchers building their first ML model, graduate students diving into NLP theory, or finance professionals mastering Python and AI for competitive advantage. My dual experience at the intersection of AI and finance ensures examples are real, context is practical, and the learning sticks.
Beyond work, my curiosity is full stack: Yale Physics, Python, SQL, GenAI, NLP, ML, 40+ countries, 5 languages, Olympic lifting, hockey, snowboarding, rollerblading, reading, and guitar. Just like my professional work, my personal pursuits are wide-ranging, rigorous, and driven by curiosity.
If you’re serious about leveling up — in your career, technical skills, or both — book a free 15-minute scoping call, and let’s explore what you need to succeed.
Steps for completing your project
After purchasing the project, send requirements so Clarence can start the project.
Delivery time starts when Clarence receives requirements from you.
Clarence works on your project following the steps below.
Revisions may occur after the delivery date.
Resume + Intake
Submit CV & Complete the intake form indicating your background, target outcomes, and frameworks you're using.
Scoping call
Free 15-minute scoping call to assess your AI/ML goals, current skill level, and tech stack.