For people who want a scheduled program with direct mentoring, not another self-paced course
I built this 18-week bootcamp to take you from following tutorials to writing Python on your own.
I teach every session myself, answer your questions directly, and notice when you fall behind. The schedule fits alongside a full-time job. $6,000/year or $500/month.
Not ready for the bootcamp? Start with the $400/year membership and see whether Reuven’s teaching approach is a good fit.
Brand new to programming? Start with the free Python for Non-Programmers course first. No membership needed.
If this sounds familiar, keep reading.
You can write code, but when you try to write Python without a lesson in front of you, you get stuck.
You’ve done the Udemy courses, the Codecademy tracks, maybe even a “100 Days of Code” challenge. While the lesson is open, it feels like you’re making progress.
Then the lesson ends, you open a blank file, and you’re right back where you started.
You’re not alone. One student described it as being “stuck in tutorial hell for almost 3 years… exhausted from all the tutorials and felt like I didn’t really learn anything except how to play and pause videos.”
Another completed a full Python bootcamp and still couldn’t read professional Python code.
Some have spent “$100 on books and Udemy courses and $3,400 on childcare” to make time for practice. And still can’t build anything from scratch.
And if you’ve started looking at the larger bootcamps, you’ve probably seen the same complaints come up again and again: expensive programs, uneven instruction, and too much distance between the student and the actual expert.
Here’s what I’ve seen training Python teams at Apple, Cisco, and Intel.
People are quick to blame themselves. But most of the time, the program they were in was designed to enroll as many students as possible and keep them moving through as fast as possible.
That is a different thing from a program designed to teach.
When enrollment is the priority, the explanations get thinner, the feedback gets pushed to assistants who are themselves recent graduates, and it becomes easy to finish the whole thing without anyone noticing what you still don’t understand.
If nobody is paying attention to how you’re doing, you can finish a program with serious gaps and never know it until you’re sitting in front of a real problem at work.
What this can look like 18 weeks from now
Picture this. It’s a Tuesday morning, 18 weeks from now.
You open your laptop, pull up a messy dataset from a real business problem, and write a script that you understand.
You understand it because you know how Python works under the hood, rather than just remembering a sequence of steps.
Your GitHub has a capstone project that hiring managers notice, built from scratch with real data and reviewed by your cohort.
Here’s what I built, and why it looks the way it does.
I’ve written three books on Python, and I’ve watched a lot of smart people go through courses, bootcamps, and self-study programs. Over and over, I hear some version of the same sentence: “I finished the course, but I still can’t build anything on my own.”
That happens because the course taught isolated pieces instead of helping students see how everything fits together. They learn enough syntax to get through the lesson in front of them, but they never get comfortable with scoping, namespacing, how objects are created, or why one approach is cleaner than another. In other words, they got a phrasebook when what they needed was a language course.
That’s why I built PythonDAB as a scheduled program: 16 weeks of content across 18 calendar weeks, with a cohort, a curriculum, and direct access to me. Every week has a topic and exercises, and every week you can ask me questions about the material and about the code you’re writing. If you need someone to beat the drum a bit, as I sometimes put it, that’s part of what you’re paying for.
I teach the material in order, you practice it every week, and if you fall behind, I’m going to notice.
How the 18 Calendar Weeks Work
Weeks 1-4: Get the fundamentals solid.
Data types, functions, scoping, and list comprehensions, with the “why” behind them so later topics don’t feel like disconnected tricks.
Weeks 5-6: Work the way professional teams work.
Git, GitHub, branching, merging, and collaboration, because writing code is only part of the job.
Week 8: Package your code properly.
Modules, packages, and PyPI. In other words, the difference between a script that happens to run on your machine and code other people can use.
Weeks 9-10: Start thinking in objects, and start working with numerical data.
Object-oriented programming and NumPy. These are foundational if you want the later data work to make sense.
Weeks 11-13: Analyze real datasets the way companies need you to.
This is a deep dive into Pandas: Series, DataFrames, visualization, dates, and multi-index work, all in the context of analysis that looks much more like real company work than classroom exercises.
Weeks 15-18: Build a capstone project around messy, real-world data.
This is where you stop following along and start making decisions yourself. You’ll use agentic AI coding tools as part of the build. The project is peer-reviewed on GitHub, and it’s meant to be something you can talk through with a hiring manager.
Weeks 7 and 14 are built-in rest weeks. That’s 16 weeks of content across 18 calendar weeks, because people have jobs, families, and the occasional cold, and pretending otherwise doesn’t help anyone.
Expect 10-15 hours per week. Everything is designed to fit alongside a full-time job, sessions are recorded, and if you miss a week you can catch up instead of disappearing entirely.
Why this works when self-paced content doesn’t
When you get confused about how a function handles variables, the root tends to be something you were never taught: the difference between local and global scope, or how Python passes objects into functions. A tutorial has no way of seeing that in your code, but in office hours I look at what you wrote, find where the understanding broke down, and we sort it out in about five minutes.
What people say about working with Reuven
Picture this. It’s a Tuesday morning, 18 weeks from now.
You open your laptop, pull up a messy dataset from a real business problem, and write a script that you understand.
You understand it because you know how Python works under the hood, rather than just remembering a sequence of steps.
Your GitHub has a capstone project that hiring managers notice, built from scratch with real data and reviewed by your cohort.
Bootcamp Graduate
“I’ve wound up with a better understanding of not just the data analytics part of Python, but also a deeper understanding of the Python commands I thought I knew well, plus a much clearer understanding of how Git operates. The Git part alone has already saved our team hours, and my improved Python has cut my time for developing!”
Norman Eliaser, Business Systems Analyst
Bootcamp Graduate
“Reuven brings together his deep knowledge about Python and its data handling features to turbo-charge your skill set.”
Sara S.
“The Intro Courses have helped me tremendously to reinforce prior knowledge and fill in a lot of gaps that I had missed or misunderstood previously. The membership is well worth the money.”
Nick Lisena, Account Manager, Logistics/Transportation
“Being part of a cohort of fellow learners over several weeks/months creates a deep feeling of belonging and mutual growth, especially for me as a full-time remote worker.”
Maria S., Senior Developer
“I benefit from having the ability to ask specific questions as part of the periodic office hours rather than spend hours searching the web.”
Lynne Thoma
One of my bootcamp students had tried another program before coming here. His comparison: “They don’t give you the support you need. They don’t give you the exercises. They don’t give you the practice.”
He enrolled in a second year of the bootcamp after that.
Who’s teaching you
I’m Reuven Lerner. I’ve been teaching Python for more than 30 years, and what I am is a teacher.
I studied computer science at MIT, and later did a PhD in learning sciences because I became fascinated by how people acquire technical skills. That combination shapes everything I build. I care about Python, of course, but I also care about how to explain it so that it sticks.
Over the years, I’ve trained teams at Apple, Cisco, Intel, Sandisk, HP, and VMware. I speak at PyCon and EuroPython, and I’ve written three books on Python. But the part that matters most here is simpler: when you join the bootcamp, there isn’t a layer of support between us. You get me.
I’m a one-person company, which means that if you ask a question, I answer it, if you’re stuck, we talk it through, and if you disappear for a week, I’m likely to notice. I’m personally available at [email protected], and I answer those messages myself.
I’ve also been learning Chinese for years, and that has influenced my teaching more than you might expect. It has reminded me how easy it is to feel like you “know” something until you have to use it, and how much practice matters.
I tell jokes when I teach, and often I’m the only one laughing. But I still find Python genuinely interesting, and if I do my job well, you’ll start finding it interesting too.
On your roadmap call, we’ll talk about where you are, what you’ve tried, and whether this bootcamp is the right fit. If it’s not, I’ll tell you.
Everything you get in your bootcamp year
When you join the bootcamp, you get full, all-you-can-eat access to everything in LernerPython for a year. The bootcamp is the backbone, but everything else is included from day one.
- The bootcamp itself:
16 weeks of content across 18 calendar weeks, with a strict weekly curriculum, exercises, and a pace that is meant to keep you moving. - A second cohort in the same year,
so you can take the bootcamp again to deepen your skills or catch up properly if life got in the way the first time. - Every office hour session,
where you can bring your questions, your code, and whatever is currently blocking you. - A private Discord community,
which gives you a cohort, a place to ask questions between sessions, and other people working through the same material. - Full access to every course,
including Python, Git, Data, NumPy, and Pandas, from day one. - The HOPPy project courses,
guided project builds where you create portfolio-ready Python applications over eight weeks. - Special lectures and extra-upgrade courses, like the agentic coding classes
I recently ran. - Bamboo Weekly paid tier,
weekly data puzzles to keep your Pandas skills sharp. - Recordings of everything,
so if you miss a session or want to review something, you can.
I include all of that because you need the right material, in the right order, with enough repetition and support to make it stick.
Time investment: Plan on 10-15 hours per week. I’ve designed the schedule for people with full-time jobs, and I built in two rest weeks because life does, in fact, happen.
The investment
$6,000/year
or $500/month for 12 months
That’s about $125 per week.
If you’re comparing this to a $15 course, it will sound expensive. If you’re comparing it to the larger bootcamps charging $10,000 to $17,000, it’s a different calculation.
Here, you work directly with me: the person who designed the curriculum, has a PhD in how people gain technical skills, and presents at PyCon and EuroPython.
For many people, the real comparison is not “Should I spend money on Python?” It’s “Which program gives me the best chance of finally doing this properly, without quitting my job?”
Course Report studies show coding bootcamp graduates report salary increases of $22,000 to $25,000. That’s the market context for what structured programs at this level can do.
Employer education benefits: According to SHRM, 45% of US employers offer tuition assistance. The IRS tax-free cap is $5,250/year… almost exactly the cost of this bootcamp. Ask your HR department this week.
Not ready for the bootcamp? Start with the $400/year membership to see if Reuven’s teaching approach is right for you.
Brand new to programming? Start with the free Python for Non-Programmers course first. No membership needed.
Guarantee
Full refund within the first month. After that, prorated for the year.
Still deciding?
Let’s talk about whether this is the right fit
The roadmap call is a conversation about where you are with Python, what you’ve tried, and what you want to do next. If the bootcamp makes sense for your situation and your schedule, I’ll walk you through how the next cohort works.
Next cohort starts Thursday, June 4, 2026.
Cohorts are small on purpose.
Not ready for the full bootcamp? Start with the $400/year membership and see if my teaching approach is right for you.
Brand new to programming? Start with the free Python for Non-Programmers course. No membership needed.