Learn the latest

AI Skills

Online with Live Instructor

Only 2 spots left for the July 10 - October 10 class!

AI in 2023: Concepts and Skills Course


- Hands-on, in-depth

- Taught by an instructor with significant teaching experience

- Similar in scope and length to a one-semester university course

- 3-1 student-teacher ratio

Primary Objectives

- Develop a confident, deep understanding of training and stochastic gradient descent

- Hands-on experience writing training loops with PyTorch

- Comprehensive treatment of every major neural net architecture and technique currently being used

- Hands-on experience using LangChain to build on existing LLMs

- Overview of the current research that will extend LLMs even further


- Basics of Neural Networks
- Training Deep Neural Networks using Stochastic Gradient Descent
- Using PyTorch
- Convolutional Neural Networks
- Recurrent Neural Networks

- Transformer Architecture (heart of an LLM)
- ML Hardware
- Generative Adversarial Networks and Autoencoders
- Reinforcement Learning
- Stable Diffusion
- Few-Shot Learning
- Zero-Shot Learning
- Prompt Engineering
- Training with Data and Model Parallelism
- Using LangChain

Current State of the Art:
- What comes after Self-Attention?
- Multi-Modal and Augmented Transformers
- Autonomous Agents
- Intelligence? (discussion)


Dive deep into the concepts behind LLMs. This course is perfect for anyone who wants to go under the hood and truly understand why the Transformer Architecture and Reinforcement Learning when applied together have unlocked the potential of AI and changed the world in the process.

With only 3 students at a time, we can roll up our sleeves and write Python code using PyTorch to describe every detail of deep learning models and LangChain to explore the latest techniques that layer on top of LLMs.

The course has been refined with the help of expert ML researchers and practicing software engineers to focus on the most important AI concepts that are relevant today.


Each class session lasts 1.5 hours with a max of 3 students. Classes are held online via Google Meet. The course consists of a total of 25 class sessions.

Hands-on Skills

- Setup your local ML development environment

- Use PyTorch starting with pre-trained models and public datasets

- Train small models from scratch to develop a confidence in understanding stochastic gradient descent 

- Learn production ready natural language processing and machine vision techniques 

- Practice hyperparameter tuning

- Learn how Reinforcement Learning (RL), Generative Adversarial Networks (GAN), and Autoencoders can be used in practice

- Design and run a small ML research experiment

- Use cloud based TPUs to train a larger network in parallel

- Use LangChain to "close the loop" on LLMs and super-charge your productivity


There are no hard prerequisites, but some experience with Python and a general STEM background is helpful.

Machine learning is a broad discipline that builds on everything from statistics and linear algebra to coding and electrical engineering. Current AI techniques draw from an assortment of concepts from each with a special focus on statistics. If you're familiar with concepts like regression, entropy, linear superposition, and dot product, you'll be fine. And if not, we are going to cover those topics in detail.

When it comes to writing code for ML, I'll cover every aspect of Python we need for the course. The ML scripts we will write tend to look similar to each other and are much simpler than traditional software engineering.

It's an intense course that requires more time outside of class for self-study if you don't already have the equivalent of an engineering or data science degree, but I work hard to find the best way to explain the core concepts and spend significant time finding high quality supporting material to fill in any gaps.

Upcoming Classes

July 10 - October 10 (morning)

Mondays and Tuesdays 9am-10:30am PT (25 total class sessions)

Location: Online (Google Meet)

Tuition: $2750 ($1000 due August 2; remainder due August 30)


2 of 3 spots remaining

August 21 - November 21 (evening)

Mondays and Tuesdays 5pm-6:30pm PT (25 total class sessions)

Location: Online (Google Meet)

Tuition: $2750 ($1000 due September 13; remainder due October 11)


3 of 3 spots remaining

Testimonials From Previous Courses

"    I was lucky to find Steve's Semi Engineering course; it was a blast. As a software person, I've always been interested in hardware. However, I never dreamed of getting started with Chip/VLSI design and eventually going through the tape-out process.

Steve is a great mentor, constantly gauging the students' understanding and adjusting his teaching style accordingly. The format combines hands-on sessions and lectures with prompt feedback, greatly accelerating the learning process.

For adult learners, Steve has a structured teaching style, dividing core concepts into chapters. Learning new skills in a short amount of time after work can be overwhelming, but he lays out the foundations and provides an overview at an appropriate abstraction level, helping students develop mental models early on.

The Open Source design flow we rely on is still in its early stages, with mostly community-maintained toolchains that originated from academia or individual efforts, which can make them a bit rough around the edges. A significant part of our capstone project involves learning to use these toolchains for design. It's easy to feel lost when navigating multiple codebases while still grasping the hierarchy of concepts, but Steve is there to help me overcome those challenges.

Steve is an avid learner who is always building and experimenting. Whether you're a beginner starting to code or an experienced professional, I highly recommend him for your next learning project."

- Ian

"    I had the privilege of being a student in Steve Goldsmith's 1-on-1 Full Stack Web Development Cohort at Aurifex Labs, founded by Steve himself, and I can confidently say that it was a transformative learning experience. Steve's approach to teaching is fully project-based, ensuring that we not only learn the concepts but also apply them in projects.

One of the most impressive aspects of Steve's teaching style is his commitment to addressing every single doubt. He patiently explains each concept until it is crystal clear, never rushing to go fast. The sessions are not bound by a strict time limit, instead Steve ensures that all doubts are resolved before concluding, even if it means extending the session.

Steve, as the founder of Aurifex Labs, provides a supportive and nurturing environment for learning. His expertise in web development is evident in every lesson, and his passion for teaching is truly inspiring. I wholeheartedly recommend Steve Goldsmith's Full Stack Web Development Cohort at Aurifex Labs to anyone looking to elevate their skills and unlock their potential in the world of web development 1-1."

- Murali

"    I was fortunate to find Steve’s one on one web development course at Aurifex Lab . Frankly, it was the best learning experience that could have happened to me. The course was highly structured and focused on programming core concepts and principles i.e data types, loops, objects, arrays, D.R.Y(Don’t repeat yourself) etc..

I’ve always been very curious about coding as I had worked in Quality Assurance testing with software engineers, but I had always thought it was out of my reach or too “difficult to learn”. I joined coding bootcamps but their teaching style was too fast paced and didn’t properly explain the key concepts that were important to understand in computer science. Steve really eased those doubts.

He starts you off with simple fun projects! (space invaders) and makes you really think about what you're coding instead of just telling you what to type. He provides you live feedback on what is going on in the back-end of the program and challenges you logically to think of the next step. Even if you do get stuck, Steve is extremely patient to help you process all of the information being thrown at you.

If you’re curious about learning web development, AI, data structure/algorithms or even looking for a change of career, then Steve at Aurifiex Labs is definitely the place for you to harness the skills needed to be adequately prepared for the job market. I can’t recommend his web development course enough. All you have to do is take the plunge of courage to tackle head on those doubts and Steve can lead you there.

”We suffer more in our imagination than in reality.” - Seneca "

- Eric

About the Instructor

Steve Goldsmith is the founder of Aurifex Labs and instructor of the AI in 2023: Concepts and Skills course.

Steve worked for 6 years as a STEM tutor and Python coding teacher including co-founding Bay Area Summer Enrichment Camp where he taught Python to over 100 students. Steve has developed games (Python/C++), audio software (C++), web applications (JS/HTML/CSS), and has an electrical engineering degree.

"     I am passionate about teaching tech skills and have been researching compilers, computer architecture, and programming languages for over a decade. My focus was on VLSI and Hardware/Software Co-Design for the past couple of years.

A few years ago I developed Prospero, a real-time source control system featuring video chat and live coding features.

My focus over the past year has shifted to Machine Learning and AI. I am now all in on using Generative AI as a force muliplier in every engineering context."

- Steve

I am not on any social media including LinkedIn. You can contact me here and read my blog here.

Resources Created By Steve

Teacher's Manual

Verilog Style Guide

External Resources

Canonical Online Resources for Students

PyTorch Tutorials (ML)

Hugging Face (ML)

Marktechpost (ML)

phind (LLM-based coding)

MDN (Web)

CSS Tricks (Web)

OWASP Top 10 (Security)

semiengineering.com (Semiconductor)


Grokking Deep Learning, Trask, Andrew

Clean Architecture: A Craftsman's Guide to Software Structure and Design, Martin, Robert

CMOS VLSI Design: A Circuits and Systems Perspective (4th Edition), Weste, Neil; Harris, David

Formal Verification: An Essential Toolkit for Modern VLSI Design, Erik Seligman, et al.

Computer Architecture: A Quantitative Approach, Hennessy, John; Patterson, David

Security Engineering: A Guide to Building Dependable Distributed Systems, Anderson, Ross

Crafting Interpreters, Nystrom, Robert

Open Source PDKs (Semiconductor)

SKY130 - Skywater 130nm PDK

GF180MCU - GlobalFoundries 180nm PDK