Learn Data Engineering Recenzje 55

I’ve had an excellent experience with Learn Data Engineering. The content is well-structured and gets straight to the point, without unnecessary filler. Concepts are explained clearly and with a strong practical focus, which is essential in such a technical field.

What I value most is the balance between theory and hands-on practice: from core data engineering fundamentals to real-world use cases and modern industry tools. This makes the learning experience highly applicable to professional projects.

The course progression is also very well designed, allowing you to build knowledge step by step, even if you start from an intermediate level. The examples are especially helpful in reinforcing complex concepts without feeling overwhelming.

Overall, this is a solid, up-to-date, and practice-oriented learning resource. Highly recommended for anyone looking to enter or strengthen their skills in Data Engineering with a serious and job-ready foundation.

As someone with little experience in the field of data engineering, I have really appreciated Andreas' approach to explaining the fundamentals and building solid foundations for the course. The content is structured logically and builds towards the eventual payoff of hands-on projects. Highly recommended!

Well, I would have to tell this is the most superficial course I have seen. This course basically doesn't teach you Python, but it tells you where you can learn Python, and we would not pay $300 just to know where to learn it. We would want the instructor to teach it firstly, so as a result I have requested a refund, but there is no option for me to even click refund or contact them. This is a very, very bad choice.

"I rarely leave reviews, but this course significantly missed the mark. Compared to other data engineering resources, the content quality was disappointing. Furthermore, the '14-day money-back guarantee' is not easy to execute; there is no option to manage or cancel the membership within the account dashboard. I’ve had to reach out via the FAQ and email, and I’m currently waiting to see if they will honor the refund policy."

I highly recommend Learn Data Engineering’s coaching program (LDECP). I shopped around and met with several other Data Engineering coaching programs before finding LDECP. I learned a lot through this process: several of the other options used third-party high-ticket sales reps (felt like a scam) and charged huge prices for what seemed like limited access/potential. But after reading DE Reddit and bouncing back and forth with AI, I came across LDECP. I was excited about it because it is led by Andreas Kretz, whom I already followed on LinkedIn and YouTube.

What convinced me to join was Andrea’s cost transparency and value proposition: you work directly with him and his team and get lifetime access to LDE’s modules, which means your learning can continue long after your coaching window ends. For me, that alone separated LDECP from the other programs I looked at.

As an already employed data engineer, I joined LDECP with a goal to transition into the finance industry. Andreas guided me through a full rewrite of my resume and showed me how to better present my professional story. After several iterations and interactions, I started to apply. I received responses that my old resume never produced. Fortunately, thanks to LDECP and the platform’s modules, I successfully navigated several rounds of interviews and accepted a new DE role in finance with increased pay and new experiences to grow.

Even after landing this role, and with my coaching window still active, Andreas has continued to help me think through new architectures and my career strategy. He and his team are extremely knowledgeable and genuinely invested in their students.

Joining LDECP was worth every f"{insert_currency_here}." If you put in the work, Andreas and the team will be there to support you every step of the way.

The coaching is very beneficial because it helps you think more clearly about architecture and how to properly design a data solution or platform. It also teaches you how to connect different tools and components effectively.
I would recommend it to anyone who wants to deepen their knowledge in data engineering and improve their overall thinking and design skills.

There are clear guidelines, lots of learning materials and opportunities to get feedback on the project. Also the pace is self determined.

Despite that, its a steep learning curve and one must put in a lot of effort to get a good final plattform.

The coaching team is always able to help out and point to the right direction if things become unclear.

I had 10 years of software engineering experience but wanted to pivot into data engineering. The field seems so broad and there are so many tools, I had a hard time finding what I need to know and how to put it all together.
Also in these difficult times, I wanted to continue to work as an external consultant which is quite challenging, when you're just starting in the field.

By coincidence, I stumbled upon Learn Data Engineering and it was one of the best investments of my life. I had 2-3 coaching sessions each week, full access to all existing and new courses, and a customized roadmap where I built a real-world project.

A few months later, I have not only learned a lot, but I also got my first two big clients in the field and will make 6-figures a year. The coaching sessions alone are worth the investment and everything else is just such a valuable bonus. I genuinely believe that everyone should consider the coaching if they want to get into data engineering.

I joined Andreas' coaching program to fill skill gaps, improve my portfolio, and prepare for new career opportunities. The program exceeded my expectations. It is incredibly valuable, 100% personalized, and gives full access to the academy's content, Andreas, and the other coaches who are always supportive. Halfway through the program, I gained a lot of confidence and was able to secure a new job thanks to the skills and confidence I acquired. The small group setting and expert advice made a huge difference, and they help you create one or more real-world personal projects, which really boosts your technical skills and confidence. I had been trying to upskill on my own before, but this program helped me accelerate my career. It is one of the best investments I have ever made. That said, success is directly proportional to your effort, so you need to commit yourself fully. Highly recommend it if you want practical, personalized guidance and results.

I've signup for different bootcamps and websites in order to learn data engineering from 0, and I must say that learndataengineering.com have the best projects for me to learn real life examples!!.
I've completed 2 projects so far and they are somekind mid difficult for me(as im a new to this realm), but they are amazing at the same time , as I can add those projects to my resume, im looking forward to do more projects to learn more and be more knowledgeable ,so I can be ready to get a job :)
I super recommend this website for learning. wow!

Andreas content helped me a lot when I was transitioning into the data engineering field

I appreciate supportive feedback that gave me direction to progress in my data engineering journey 😇.

I really enjoy learning the new/cutting edge tools and courses in data engineering from Learn Data Engineering Academy and I highly recommend other data engineering aspirants to take the Academy's membership!

I joined Andreas’s coaching program to deepen my understanding of data engineering, and it exceeded my expectations. This course offers incredible value for anyone looking to accelerate their ability to design and implement data pipelines effectively. Whether you’re an experienced practitioner or an application developer transitioning into data engineering, you’ll find gaps to fill and new approaches to refine your skills. The small group setting, where you can work on a project of your choice, makes the experience highly personal and directly applicable to real-world challenges. The real differentiator is the access to experts and the supportive community, which provides extremely valuable feedback and guidance. Like any technical discipline, the more effort you put in, the more you’ll gain. Invest in yourself and take your data engineering skills to the next level.

The teaching team and content is very good. There is a LOT of material, so you need to stay serious and devoted to complete it all. I finished most of the material, but need to complete some of the capstone projects. I highly recommend joining the Academy and following Andreass on Youtube. I purchased the unlimited access (no expiry) which I really suggest.

I subscribed to the lifetime learning platform along with the 6-month coaching program. Coming from a data analyst background (BI tools, Python, Excel, and SQL), I had no prior experience with data engineering tools.

1) Review of the 6-Month Coaching Program:
- Personalized learning path: Trainers provide customized modules based on my skills and local job market demands, including a structured learning plan and tailored projects like OLTP, OLAP, or ML-based projects.
- Career development support: Beyond technical skills, trainers guide resume enhancement, GitHub improvement, blog writing, and job interview strategies from real-world experience.
- Expert trainers from diverse backgrounds: The three trainers specialize like in GCP, AWS, dbt etc and coming from both corporate and startup environments.
- Weekly coaching calls & Discord support: Group calls allow live Q&A, though experienced learners might find waiting times long. Discord DMs provide quicker, direct support.

Benefits:
- Real-world guidance: I gained valuable insights from experienced data engineers, learning both technical and industry best practices in a supportive, non-gatekeeping environment.
- Identifying blind spots: Trainers pointed out overlooked areas like throttling in streaming pipelines and data governance, helping me improve design and documentation skills.
- Confidence in project design: My OLTP/OLAP designs were reviewed and validated by industry professionals, boosting my confidence.

Challenges:
- Misconception about coaching vs. bootcamp: Initially, I expected structured evaluations but later realized coaching is self-driven guidance, not a step-by-step course.
- Time zone differences: Calls were late at night for me, making myself less productive. But I endure tho.
- Self-learning required: Solutions aren’t spoon-fed; independent problem-solving is essential.

2) Review of the Learning Platform:
- Clear and concise content: Modules are broken into short videos, making complex topics easier to grasp. Andreas does a great job of visualizing workflows (e.g., his “Data Science Blueprint”).
- Wide coverage from basics to advanced topics: Covers Python, security concepts, OLTP/OLAP projects, and cloud platforms (AWS, Azure, GCP).

Benefits:
Simplified explanations: Topics like data modeling are broken down for easier learning.
- Lifetime access & diverse tools: Useful for refreshing skills whenever needed.

Areas for Improvement:
- More content on scaling & system design would enhance the end-to-end learning experience.
- Limited open-source tool coverage, though projects naturally introduce complexity over time and makes sense no platform can ever support such details yet.

Final Thoughts:
This program exceeded my expectations as aspiring data engineer, offering real-world coaching, hands-on projects, and career guidance or even use coaching as consultation session instead. I’d highly recommend it for self-motivated learners ready to put in the effort! DO NOT join coaching if you are hoping to get A-Z code along support and does not have solid time commitment for the project. DO subscribed the learning platform first instead if that the case.

I am using the platform for quite a while since i got lifetime upgrade. The platform is very good detailed course for everything and tool with regular updates and addition to the library. The author is fairly active on discord .

the suggested curriculum, the fact of using containers, github and the projects at the end of the course is much more attractive than many courses I have already tried to take.