SuperDataScience Bewertungen 102

AI Engineering program, and it’s been an incredibly rewarding experience. The structured, hands-on approach makes complex concepts feel practical and achievable, while the consistent progress each week keeps motivation high.

AMAZING! Kirill and team make sure we understand everything in depth!!

The company helps me with clear videos and the possibility to ask questions anytime to get a good start within AI programming. I love the positive way. There are plenty of redoings in different ways, to help not just understand but also remind, how to succeed. You build a complete application which might be useful for the future and get a lot tipps to do well.

Hands-on exercises with step-by-step instructions of some of the key functionalities in areas of analysis (2D, 3D), tool callings, RAG-based development, token usage, and utilizations, and many other critical kinks useful for any applications when using LLM models. Above this, I enjoyed a weekly team meeting that helped me understand the challenges and how other teammates were doing. I really enjoyed it, and it was worth the time spent in this course. Thanks, Kirill and the team, for the fabulous course.

Real coding and fun to work with Kirill.
Real RAG and vector database
Calling tools is so fun

This course was really worth every penny, thoroughly enjoyable and video tutorials were very informative. I have a feeling this will be the perfect start to my AI career and I could not recommend SuperDataScience highly enough.

I joined the SDS 6-week AI Challenge. Our cohort just officially hit the halfway point and the learning curve has been exhilarating!
These past 3 weeks have been about moving beyond the "chat box" and into the realm of robust, production-ready AI engineering!
This program has already reshaped how I think about building with AI.
I came in with foundational knowledge, but the depth of what we've covered has been genuinely eye-opening.
More than invoking LLMs through APIs, this program teaches how to manage context, orchestrate tool calling and responses, structure your cost model and design for non-determinism are what separates a prototype from a real product 🏆

Three more weeks to go, and I'm excited as I continue to refine my 'Digital Twin'.

Really enjoyed the SuperDataScience AI Engineering with Digital Twin program. Nice bite-sized learning cadence with content and exercises that start small and then are expanded upon. Kirill, his staff, and the learning environment/community help you stay engaged and wanting to come back daily to progress in your learning journey.

My next job role is becoming clearer to me now. It’s not an MLE, or data scientist, but an AI Engineer (or AI Engineering Manager). I have been going back and forth for some time now, but hands-on learning and working with the actual AI tools provided clarity. Then, when you read the articles on potential career paths, it makes so much more sense. This 6-week AI sprint, along with other AI/ML courses and foundational reading, supported by hands-on learning, is a winning combination for anyone who wonders, “What’s next?" For me, it looks and feels like AI Product / AI Engineering - I would like to do both to become well-rounded. Once again, great course.

This was a great step by step training to learn API and tool calls, incorporate AI responses, embed your resume into a chatbot and stand out to recruiters with something different!

I love how Kirill makes this easy to follow along.
The weekly check-ins really helped me to stay motivated to keep up with the work!

I had a really good experience with this AI Engineering course. One of the most interesting parts for me was building my own digital twin project. It made the course feel practical rather than just theoretical, because I was not only learning concepts but actually applying them in something creative and useful.
The course helped me understand how modern AI systems work, especially around LLMs, APIs, prompting, tool calling, and building real-world applications. I liked that it was structured in a way that made even complex topics feel manageable. Step by step, I was able to go from learning the basics to creating something that felt like a real product.
Building the digital twin was definitely a highlight. It was exciting to see how AI can be shaped to reflect communication style, knowledge, and behavior in a personalized way. That project gave me a lot more confidence in working with AI systems.
Overall, I think this course is a great choice for anyone who wants hands-on experience in AI engineering instead of only watching theory. It gave me both practical skills and motivation to keep building more projects.

Their courses and training are great, easy to understand. The support is excellent. I recommend SDS to anyone wanting to get into data science or improve their current skills.

⭐⭐⭐⭐⭐ Highly Recommended – Real AI Project Experience in Just 6 Weeks

I’ve just completed the SDS AI Challenge – 6 Week AI Project, and I can confidently say it exceeded my expectations.

This is not a passive course. It’s a structured, hands-on AI build sprint. Over six weeks, I developed a fully functional AI project, implementing core concepts such as:

Retrieval-Augmented Generation (RAG) pipelines

Embeddings and vector search

LLM integration workflows

Practical Python implementation

End-to-end AI system design

What makes this program exceptional is the execution focus. Instead of just consuming theory, you actually ship a working AI solution. The weekly structure keeps momentum high, and the community aspect adds accountability and motivation.

If you're serious about moving from “learning AI” to building real AI systems, this challenge provides a strong practical framework to do so.

Highly recommended for developers, data professionals, and anyone wanting real applied AI experience.

I joined the 6 weeks AI Challenge. This program is very well designed. If you don't know anything about AI you will learn it here. The program is catered for both people who are new to the field and people who know a bit about it and want to know how to build and deploy a digital twin. The best part it takes 30 minutes of your time everyday. To learn a new skill in 30 minutes over 42 days is an amazing feeling.

I always wanted to learn about AI and build a real world AI project. Kirill and the superdatascience team are helping me with that goal. I am happy with the progress I've made so far and look forward to more learning with superdatascience.com

If you're also starting out with AI, I'd highly recommend checking out superdatascience.com

Thank you Kirill and superdatascience team!

The FinResearch AI project was a very positive experience. It was especially valuable to observe how more experienced AI developers think, structure their work, and communicate within a project setting. The collaboration provided meaningful insight into real workflows and problem-solving approaches, even through a beginner's eyes.
The overall exposure was highly motivating and encouraged further learning and development. Participation in future collaborative projects would be very welcome.

What is great about SDS is its overall ecosystem with courses, projects, and most importantly, people. There are many sites where you can learn courses with videos, and there are other places where you can get projects, but here we get both of them in the best way possible. And this is not even the best part of SDS. There is actually a sustained weekly mentorship. Data science and AI are vast areas, and most of us are not exactly sure what career path we should follow. There are boilerplates on the internet, but all of them cannot fit in the same box. Some are starting out, others are mid-career, and still others are in senior roles. Personal mentorship from SDS helps here. SDS is an amazing setup. I am glad I found it.

SuperDataScience has been an incredibly valuable part of my data science journey. While the training courses are well-structured and informative, the real learning happens in the collaboration projects. Working on real-world problems alongside other learners has pushed my skills forward in ways that traditional courses alone simply can’t.

The collaboration projects are thoughtfully designed and feel authentic — you’re not just following instructions, you’re thinking, experimenting, and learning how real data science work is done. That hands-on experience has been the most impactful part of the program for me.

I also can’t say enough positive things about the project management support. My PM, Shaheer, has been fantastic — knowledgeable, patient, encouraging, and genuinely invested in helping each team member succeed. His guidance, responsiveness, and ability to explain concepts clearly make a huge difference, especially when tackling more complex material.

If you’re serious about learning data science and want more than just videos and theory, SuperDataScience’s collaboration projects are absolutely worth it. I highly recommend the program to anyone looking to build real skills and confidence in a supportive, well-run environment.

My journey with SuperDataScience began through their highly acclaimed ML A-Z course on Udemy, taught by Kirill Eremenko and Hadelin de Ponteves. I was immediately impressed by their deep subject matter expertise and exceptional teaching methodology.

Subsequently joining the SDS community proved to be one of the most valuable professional decisions I've made. The platform is specifically tailored for data scientists, machine learning engineers, and AI practitioners. Beyond their extensive library of exclusive courses, the thriving community of over 5,000 members provides unparalleled opportunities for professional networking and peer collaboration within the field.

A particularly noteworthy aspect of the SDS community is their structured collaborative project initiatives. These projects provide practical application opportunities, allowing members to translate theoretical knowledge into real-world solutions. The combination of hands-on experience, expert guidance, and weekly project discussions creates an ideal learning environment that effectively bridges the gap between academic concepts and practical implementation.

Additionally, the platform demonstrates strong commitment to member engagement through their monthly incentive program, featuring a generous $500 prize draw for five winners.

SuperDataScience offers an exceptional ecosystem for continuous learning and professional development. I highly recommend this platform to anyone serious about advancing their career in data science and AI.