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Made With ML

Applied ML · MLOps · Production

Join 30K+ developers in learning how to responsibly deliver value with ML.

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🏆  Among the top ML repositories on GitHub.
❤️  30K+ community members and growing.
🛠️  Highly recommended industry resource.

Made With ML

MLOps Course

A project-based course on MLOps fundamentals with a focus on intuition & application that teaches you how to apply ML in industry. All the lessons below are 100% free but we also offer a highly interactive 6-week course where you'll learn how to master MLOps.

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Upcoming cohort:
Sept 18th, 2021

Who is this course for?

Machine learning is not a separate industry, instead, it's a powerful way of thinking about data that's not reserved for any one type of person.

Software engineers
looking to learn ML and become even better software engineers. ML is integrated into increasingly more products so it's important to know how ML systems operate.
Data scientists
who want to want to go way beyond developing models in a notebook to wrapping them around robust workflows that enable ML systems to improve over time.
College graduates
looking to learn the practical skills they'll need for the industry and bridge gap between their university curriculum and what industry expects them to know about ML systems.
Product managers
who want to develop a technical foundation in MLOps so they can effectively communicate with their technical team and help develop and iterate on applications.

Foundations

Learn the foundations of machine learning through intuitive explanations, clean code and visualizations. → GokuMohandas/MadeWithML

🛠 Toolkit
🔥 Machine Learning
🤖 Deep Learning

MLOps

Learn how to apply ML to build a production grade product and deliver value. → GokuMohandas/MadeWithML

📦 Purpose 🔢 Data 📈 Modeling
📝 Scripting 📦 Interfaces ✅ Testing
♻️ Reproducibility 🚀 Production

Wait! All the lessons are 100% free?

Yes. The lessons above are 100% free and you can learn all the fundamentals of MLOps by going through them. So what exactly is the paid course for? It's extremely difficult to learn things on your own without the proper structure and experience, especially complicated topics such as MLOps. So we're offering the exact structure and experience you need to master the MLOps fundamentals in just 6 weeks. Yes, 6 weeks is more than enough.

⚡️ Live lectures
Interactive sessions to deep dive into concepts from a top-down approach using visualizations.
💻 Coding workshops
Applying MLOps concepts by learning how to produce high quality, production-grade code in our project.
❓ Q&A
Opportunities to ask questions and have discussions after every single module before we progress.
🧭 Navigation series
Guiding sessions on how to approach ML research papers, Python libraries and your career.
🌎 Community
Alumni community to ask questions, share your work and get feedback and continue your learning journey in this ever-changing field.
🚀 Career assistance
Resume and portfolio reviews and mock interview practice to ensure you land your dream job (premium plan).

Course deliverables

We will be applying the concepts we learn each week to iteratively complete two deliverables. One will demonstrate your technical skills while the other will showcase your communication and domain expertise through a written piece.
💻 End-to-end repository
It's not enough to just learn about concepts at a high-level, so as we learn each concept, we will be building onto our end-to-end ML project from modeling to CI/CD. We will be learning the concepts from a first principles approach and develop the mental frameworks to be able to adapt to any context (tech stack, platform, tools, etc.).
✍️ MLOps in "X"
Writing is a very important skill, so as we learn each concept every week, we will be writing about how the concept applies to "X", where X is an industry (or even a specific task) that you're passionate about. By the end of the course, you'll have a well written, and reviewed, piece to share with the community that will be the start to establishing yourself as an expert in ML applied to "X".

⚡️ Your new superpowers ⚡️

With live lectures, coding workshops, interactive discussions, you'll attain a:

Foundational ML expertise to architect an ML system using best practices, articulate your knowledge to others and continuously adapt to this evolving space.
Ability to compose high quality code to create robust ML systems that you, your future self and fellow developers will come to greatly value as you iterate and develop.
Community to continue the journey and grow via discussions on new tools and best/bespoke practices, collaborate on projects and share your progress regularly.

Meet your instructor

Hi, I'm Goku Mohandas

Over the past 7 years, I've worked on ML and product at a large company (Apple), a startup in the oncology space (Ciitizen) and ran my own startup in the rideshare space (HotSpot). Throughout my journey, I've worked with brilliant developers and product managers and learned how to responsibly develop, deploy and iterate on ML systems across various industries.

I currently work closely with early-stage and mid-sized companies in helping them deliver value with ML while diving into the best and bespoke practices of this rapidly evolving space. I want to share this knowledge with the rest of the world so we can accelerate progress in this space.

ML is not a separate industry, instead, it's a powerful way of thinking about data, so let's make sure we have a solid foundation before we start changing the world. Made With ML is our medium to catalyze this goal and though we're off to great start, we still have a long way to go.

📅 Schedule

This course runs from Saturday, September 18th 2021 to Saturday, October 23th 2021. However, the fundamental skills you develop and the community will be yours forever.

Week 1️⃣

Saturday
Sept 18th, 2021
7 am - 10 am PT
Sunday
Sept 19th, 2021
7 am - 10 am PT

Week 2️⃣

Saturday
Sept 25th, 2021
7 am - 10 am PT
Sunday
Sept 26th, 2021
7 am - 10 am PT

Week 3️⃣

Saturday
Oct 2nd, 2021
7 am - 10 am PT
Sunday
Oct 3rd, 2021
7 am - 10 am PT

Week 4️⃣

Saturday
Oct 9th, 2021
7 am - 10 am PT
Sunday
Oct 10th, 2021
7 am - 10 am PT

Week 5️⃣

Saturday
Oct 16th, 2021
7 am - 10 am PT
Sunday
Oct 17th, 2021
7 am - 10 am PT

Week 6️⃣

Saturday
Oct 23th, 2021
7 am - 10 am PT
  • Product and project management
  • How to continue the learning journey
  • How to continue building personal brand

Every week

Tuesdays
9 am - 10 am PT
(optional)

Ask questions about anything!

  • Doubts about any concepts
  • Assignment feedback
  • Personal project guidance
Thursdays
4 pm - 5 pm PT
(optional)

Ask questions about anything!

  • Doubts about any concepts
  • Assignment feedback
  • Personal project guidance

After the course

Continue your learning journey with the alumni community!

  • Work on portfolio projects and get feedback.
  • Participate in reading & study groups to stay up-to-date.
  • Collaborate to build the next great product that's made with ML.

Learn how to responsibly deliver value with ML.

Upcoming cohort:
Sept 18th, 2021

Free

  •  Self-paced detailed lesson blog posts
  •  Production grade code in every lesson
  •  Visualizations to illustrate every concept

$0 USD

Get started

Essential

  •  Master MLOps in 6 weeks
  •  Live sessions and coding workshops
  •  Live Q&A office hours
  •  "How to navigate X" series (ML research, Python libraries, career)
  •  Alumni community

$1,250 USD

Apply

Premium

  •  Everything in the Essential plan
  •   90 min. 1-on-1 session for career and project guidance.
  •   In-depth instructor review of course deliverables.

$2,000 USD

Apply

ENTERPRISE We also offer an accelerated 2-3 day live workshops with team project-based guidance (tooling, infrastructure) for enterprise customers which we've delivered across teams at Apple, Google and many other Fortune 500 companies, as well as early-stage startups to ensure they're aligning themselves for success. Reach out to us if your team is interested.

Reimbursement

Our alumni have had a lot of success getting 100% of the course reimbursed by their employers since all of this directly falls under career development and, in many cases, immediately necessary for their work. After you apply and are accepted for a cohort, check out this email template that we've put together that you can send to your manager to get this course reimbursed.

💸 Money Back Guarantee 💸

If you attend the live sessions and complete the deliverables yet still don’t find the course valuable, we’ll refund 100% of your payment within 30 days of the start of the course.

Frequently Asked Questions (FAQ)

  • Software engineers looking to learn ML and become even better software engineers. ML is integrated into increasingly more products so it's important to know how ML systems operate.
  • Data scientists who want to want to go way beyond developing models in a notebook to wrapping them around robust workflows that enable ML systems to improve over time.
  • College graduates looking to learn ML and become even better software engineers. ML is integrated into increasingly more products so it's important to know how ML systems operate.
  • Product managers who want to develop a technical foundation in MLOps so they can effectively communicate with their technical team and help develop and iterate on applications.
After the live lectures, coding workshops, interactive Q&A and discussions, you'll attain a:
  • Foundational MLOps expertise to architect an ML system using best practices, articulate your knowledge and continuously adapt to this evolving space.
  • Ability to compose high quality code to create robust ML systems that you, your future self and fellow developers will come to greatly value as you iterate and develop.
  • Community to continue the journey and grow via discussions on new tools and best/bespoke practices, collaborate on projects and share your progress regularly.

During the first weekend of the course, we're going to cover all of the Foundations lessons. We'll be doing this fairly quickly so we can focus on the MLOps content shortly after. While we will cover the foundations of Python and deep learning, it's highly recommended to be familiar with the following:

  • Python (variables, lists, dictionaries, functions, classes)
  • Scientific computing (NumPy, Pandas)
  • PyTorch (nn.module, training/inference loops)
  • ML/DL (basics of regression, neural networks, CNNs, etc.)
You can still do the course without these prerequisites but we highly recommend that you get started with the free lessons before the course begins.
Depends on who you're learning it from. It's important to learn this content from people who've actually deployed ML to production because they'll help you develop the frameworks needed to approach difficult concepts now and beyond the course. We'll be walking you through all the concepts from a foundational perspective, then stepping into code so we can actually apply it and extend it to our own work. We've delivered this course as an accelerated workshop to many corporate teams who were able to use the experience to immediately build/improve their ML workflows.
Machine learning is increasingly incorporated into many products and so companies are looking for people with increasingly deeper knowledge on not only modeling, but how to operationalize it (MLOps). It's a major advantage to understand the fundamentals of this field at this nascent stage so you can responsibly deliver value with ML as a foundational developer in your industry.
Absolutely, this course is meant for busy people who are building things, which is why all the sessions are during the weekend.
It's highly recommended that you attend the live sessions because the interactive structure and experience is what makes mastering all this content possible. However, sometimes things happen that are out of your control, so we will provide recorded sessions that you can watch on your own time and then use the community to ask questions so you can catch up.
During the week, you should practice the content that we covered over the weekend. This involves re-implementing the code, digging into the additional resources and engaging in discussions with the community.
After the course, you'll have all the MLOps fundamentals you'll need to build a robust ML application. You can work solo or work with peers you've met during the course to work on portfolio projects or even build your own product. Many other students also continue to engage with the community to have weekly discussions about what's new in the field, interview preparations, etc.
This course covers the fundamentals of MLOps that will easily extend to any type of container-orchestration system, cloud provider, etc. We don’t explicitly use any of these because different situations call for different tools, even within the same company. So it’s important that we have the foundation to adapt to any stack very quickly, as opposed to be being too strongly tied to any one technical stack.
Yes, this course is 100% remote which means no travel but you'll meet fellow students from around the world and learn from each other.
If you're not 100% satisfied by the end of the first weekend, we'll refund 100% of your payment.

More questions?

Feel free to send us an email with all your additional questions and we'll get back to you very soon.

To cite this content, please use:

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@misc{madewithml,
    author       = {Goku Mohandas},
    title        = {Made With ML},
    howpublished = {\url{https://madewithml.com/}},
    year         = {2021}
}