Liora Reviews 

When I asked to return a poor quality item, I received this reply.

Reply:
I've read everything you've written and I'm not going to argue any of it back at you.

On what I can actually do. £4.00 back on your card, with the CAMILA staying with you — paid within a few working days, nothing for you to package or post.

On a returns label at our cost: we don't issue one. Not for you specifically and not for anyone — there's no such system here, so it isn't a decision being made about your order. I'd rather tell you that plainly than let you wait for something that isn't coming.

The return itself is open to you and here's what it involves. You post it tracked, which is £15 to £20, with a customs declaration. Then roughly five weeks before it arrives and is checked in, and the full £39.95 is released — so early October. You'd get the whole £39.95 back, and you'd have spent £15 to £20 of your own getting it there.

Side by side: £4.00 this week and nothing to do, or around £22 net in October with a trip to the post office and a customs form.

And an unworn asymmetrical dress in a 2XL isn't worthless to you either — that's the part of the resale market that's short of stock, and it moves.
If you'd still rather send it back, tell me and I'll set it up for you.

DO NOT BUY FROM THIS WEBSITE.

Rating: ★★★★★

I joined Liora's Analytics Engineering program (600 hours, certified
through Sorbonne School of Economics) fully funded via the
Bundesagentur für Arbeit, and it was one of the best decisions I've
made for my career.

The technical content is thorough — Python, SQL, Snowflake, Power BI,
dbt, Airflow, machine learning — validated through more than 30
certified practical exams, not just quizzes. By the end I had built
three real end-to-end projects I could put directly into a portfolio.

What I want to highlight, because I think it's underrated: the support
from the Program Managers. Intensive training like this isn't always
smooth, and there were moments I struggled. What made the difference is
that the team actually adapts to your situation instead of just moving
on without you. A lot of people assume that if you fall behind in a
program this intensive, there's no way back — that wasn't my
experience at all.

I finished with three certifications (Analytics Engineer, ETL
Developer, Data Analyst) and I'd recommend this program to anyone
serious about breaking into data analytics or engineering.

I completed the Data Engineering program at DataScientest, and it was a truly valuable learning experience. The curriculum combines in-depth theoretical masterclasses with practical, industry-inspired projects designed around real-world business scenarios. Coming from an 11-year background in .NET software development, this program helped me successfully transition into Data Engineering while expanding my expertise in modern data technologies and data pipeline development.

One aspect I especially appreciated was the outstanding support provided by the Program Managers. They were always responsive, understanding, and willing to help whenever I faced scheduling challenges or needed guidance. The program is intensive, but the team genuinely works with students to find solutions when personal circumstances require extensions or adjustments.

Another strength of the program is its well-structured assessment process. Every module includes a professional assignment that must be successfully completed before progressing. Passing all required assignments is an important step toward earning the certification associated with the program and the university certificate. If you don't pass an assignment on the first attempt, you have multiple opportunities to try again. If additional support is needed, the Program Managers arrange extra sessions with mentors who explain the concepts in more detail and guide you through the areas where you are struggling. This level of support gave me confidence that the goal was not simply to evaluate students but to help them succeed.

The career support is equally impressive. After completing the academic requirements, the Career Services team helps refine your CV, improve your LinkedIn profile, prepare for interviews, and provides guidance throughout the job search process. Their encouragement and practical advice make a real difference when transitioning into the job market.

The hands-on projects gave me practical experience with Python, SQL, Apache Airflow, Docker, Apache Spark, ETL/ELT pipelines, workflow orchestration, automation, monitoring, cloud technologies, and deployment. Throughout the program, the mentors played a significant role by providing technical guidance, answering questions, and ensuring that students received support at every stage of their learning journey.

Overall, I highly recommend DataScientest to anyone looking to transition into Data Engineering or strengthen their technical skills. The combination of high-quality teaching, practical projects, dedicated mentors, exceptional Program Managers, and comprehensive career support creates an environment where motivated students have every opportunity to succeed. If you are willing to put in the effort, you will find excellent learning resources and a team that is genuinely invested in your success.

I recently completed the Data Analyst program at Liora and had a very positive overall experience:)

The content was well-structured, practical, and focused on real-world data skills such as SQL, Python, and data visualisation. It helped me build a strong foundation and apply concepts directly through practical exercises and projects.

The teaching team was consistently supportive and responsive, always willing to clarify doubts and provide guidance when needed. This made my learning process smoother and more motivating.

The platform itself was user-friendly and easy to navigate, which allowed me to stay focused on learning without technical distractions.

Overall, the program had a clear impact on my professional development. It strengthened my analytical thinking and gave me the confidence to pursue data analytics roles with a practical skill set. At the end, big thanks to Lucas, Malak, Arsi, and the entire Liora team for supporting me throughout this journey:)

Comprehensive, practical, and career-changing.

I completed three programs with Liora —
Data Engineer, Data Ops, and Cloud Engineer —
all accredited by the University of Paris I:
Panthéon-Sorbonne.

What set this apart was the project-based approach.
I didn't just learn tools — I built and deployed
real systems. My graduation projects include a
full-stack ML platform and a complete DevOps
infrastructure running on a public IP with CI/CD,
Docker, and live monitoring.

For anyone looking to make a real career transition
into Cloud Engineering or Data Engineering,
this is the right investment.

I came from a creative background in advertising and wanted to add real technical skills without starting from zero. Liora was the right place for that.
I did both the Data Analyst and Data Marketing & AI modules as bootcamps, back-to-back and full-time. What made it work: the project-based approach. You don't just learn the course materials; you work with real datasets and defend real projects. I presented my final projects on real data from Stade de France (Rugby World Cup, Paris 2024 Olympics) and mycomm.com. l can only confirm that hands-on experience is what actually sticks.
If you're considering a career shift into data, especially from a non-technical background, I'd recommend it.

I followed the DevOps Engineer program when the school was still called DataScientest, before the rebrand to Liora, and I would like to share an honest review of my experience.

For me, the training was good but also challenging. I did not come from a very strong background, so some parts were difficult and I had to invest a lot of time and energy to keep up. However, the content was rich, the learning path was well structured, and the program pushed me to really learn. I studied a lot, completed the final project, passed the exams, and obtained the certifications I needed.

What made the biggest difference for me was the human side of the school. The team was always helpful, responsive, and respectful. Whenever I had a question or needed support, they answered and tried to find a solution. I especially want to thank Nicole for her support, patience, and kindness during my journey.

One important point for future students is that the program is flexible. If you are motivated but also have other responsibilities in life, this matters a lot. The platform gives access to many materials, exercises, and answers so you can learn independently and check your progress. In my case, they were also very flexible even after the official end of the course and allowed me to continue accessing the platform so I could keep studying. I really appreciated that.

I have not yet found a job in this field, so I cannot judge the program only by employment results. But in terms of learning quality, support, and flexibility, I had a very positive experience and I would recommend it to people who are ready to work seriously and learn.

I recently completed the Data Science and MLOps programs and want to highlight the excellent support provided by the Program Management team. Their responsiveness and guidance made the learning experience smooth and well‑structured. I also appreciated the quality of the training content, the helpful mentors, and the Career Management team, who offered valuable advice throughout the journey. Overall, the combination of strong program management, solid instruction, and career support made this a very positive experience.

I am Thomas Röder, I have decided to do a bootcamp with Liora Institute, Paris, France, taking the full-time Data Engineering course to improve my knowledge and understanding of best Data Practices and Artificial Intelligence landscape that is currently shaping the market.

It was the most wonderful experience ever, extremely flexible and I would recommend to anyone to take a course with Liora institute.

Thanks to Liora, I was able to get a now job for a California, US company in the Al field as a Lead Solutions Engineer for Al development and global markets.

I decided to enroll thanks to Corinna, who was incredibly helpful in clearly explaining the entire process of studying Data Engineering full-time at Datascientest. Throughout the program, Nicole Lucerni and her team provided outstanding support and truly helped ease my concerns - especially during a period when I was unwell and fell behind on some modules. Their genuine care for students really stood out.

One of the aspects I appreciated most was the flexibility Datascientest offers, allowing students to progress at their own pace without unnecessary pressure. The curriculum is modern and well aligned with current industry needs, particularly in today’s rapidly evolving AI-driven market.

I can wholeheartedly recommend this bootcamp.
Thank you for a great learning experience.

- Thomas Roeder (Founder of selenaCAT.com)

I recently completed the Data Scientist bootcamp at DataScientest, and the experience was excellent — exactly what I was hoping for.
The program covers a wide range of topics, from foundational machine learning concepts to more advanced subjects, giving a solid, well-rounded understanding of the field.
I was also impressed by the organization and structure of the lessons. The platform makes it very easy to follow the modules, track progress, and revisit materials whenever needed. Everything felt well thought-out and intuitive.
The instructors and support team were consistently helpful, responsive, and knowledgeable, which made learning even smoother. The hands-on projects were particularly valuable, helping to apply the theory to real-world scenarios.
Overall, I strongly recommend this bootcamp to anyone looking to gain strong ML engineering skills in a structured and engaging way.

The program managers were phenomenal. It wasn't just about administrative support; they were genuinely invested in our success. There were times when the material felt overwhelming, and having that accessible, personalized guidance whether it was a quick check-in or detailed advice on a project made all the difference. It transformed a challenging academic experience into a manageable, highly effective career launchpad. If you're looking for a program that pairs top-tier content with unbeatable support, this is it.

DataScientest delivers top-quality, practical training. The instructors are outstanding—clear, supportive, and always available when you need help. The platform is smooth, the projects are real-world, and the support team keeps you on track from day one. I finished the program feeling confident, skilled, and job-ready. I highly recommend it!

The Bootcamp gave me a strong foundation to transition into Data Science after years in operations. It combined solid technical training with a real sense of purpose through applied projects. The instructors were approachable and patient, and the career support was outstanding — from feedback on my CV to ongoing guidance about how to position myself for new roles. It made the whole experience feel complete.
I’m already planning to take a specialization course with DataScientest to continue developing my skills.

I took the Data Engineering course with DataScientest, because I liked the syllabus which covered the most important tools and frameworks in Data Engineering as I knew, coming from an Analytics Engineering background. The structure of the learning material is really well done. Each module describes the tool/framework from introduction to advanced usage and along the way you practice the important commands to understand what it can do and when to use them. At the end of each module there is a exam, which is quite extensive and evaluates well if you understand the course material. So far so good, however, you need to be prepared, that 95% of this course is self-studying (reading, coding, doing the exams) The other 5% are master classes, which are lectures that are related to the current sprint topic studied. I think you can make the most out of it if you connect with your peers and help each other, because when it comes to the instructors you very often have to message them more then 3 times and wait days or weeks for a reply. This is really sad, given the course costs almost 10K. So the the instructors are spread really thin and you have to look for support somewhere else. The other thing that was on the smaller side, but quite annoying was that the course material was evidently translated from French to English and not proof-read. So some sections are not very comrehensive and this will make you struggle for a bit, if you don't know the material. That is why I will give it only 3 stars. The structure is great, but the accessability for contextual and tech support on the lower end, as well as the translations of the modules.

Très belle expérience de formation sur quasiment 2 ans avec le cursus Machine Learning Engineer. Bon compromis entre l'autonomie et l'accompagnement pour rester motivé. Le projet était très sympathique à rendre !

The content of the module undoubtedly covers the most important aspects of Machine Learning and MLOps. The final project allows you to put into practice all the knowledge gained throughout the course, which makes the learning experience very hands-on and applicable. The support and attention from the staff are also excellent.

I come from marketing with over 15 years of experience - 6 years as Head of Marketing at Posterlounge and most recently as Marketing Director at Brandible.

Throughout the past decade, I've been drawn to data: analyzing campaign performance across channels, optimizing KPIs, turning insights into strategic decisions. I went beyond spreadsheet formulas and taught myself JavaScript, then Python, to automate campaign optimization, product catalogue management and reporting.

When my self-taught coding hit the limits of what I could accomplish while working full-time, I decided to formalize my skills. DataScientest Data Science bootcamp provided exactly what I was seeking in the format I needed: online and intense.

What I appreciated was the hands-on approach. Working on challenges like the Rakuten e-commerce classification project gave me experience with the complete pipeline - from text and image preprocessing to implementing NLP and computer vision models. The program covers everything: Python, Linux, machine learning, deep learning.

Make no mistake: The program is intense and demanding. While there are challenges - outdated materials, translation gaps - the core learning was solid.

My advice: don't overuse AI. Don't copy-paste. Don't just study for exams. Instead: invest time understanding fundamentals.

I completed an intensive bootcamp-style program where I deepened my skills in Python, data visualization, machine learning, and deep learning. The self-paced structure required strong motivation to keep up, but it made the journey even more rewarding.

Overall, the program was a great learning experience, and I’m now eager to further expand my expertise and put my skills into practice.

As a seasoned software engineer with many years of experience, I was looking to refresh my IT skills and deepen my knowledge in data-related technologies. I recently completed the Data Engineer program with DataScientest, and it has been a very rewarding experience. The curriculum is well-structured and up to date, striking a good balance between theory and hands-on practice, which allowed me to strengthen my expertise and learn new approaches step by step.

The teaching team was always available and supportive, providing quick, insightful answers and guidance whenever I needed it, which really helped me stay engaged. The platform itself is intuitive and user-friendly, making the learning process smooth and efficient.

Most importantly, the program has had a significant impact on my professional development: it gave me the opportunity to refresh and expand my skills, gain confidence with modern data engineering tools, and stay relevant in an ever-evolving tech landscape. I would strongly recommend DataScientest to experienced IT professionals who want to broaden their expertise, as well as to those starting their journey in data.