Artefact School of Data Reviews 94

Although I started from scratch in this field, the course is so well prepared that it helped me to have all the necessary basic information. Lack of a possibility to use the information received at the end of the course in a company environment.

Very interesting bootcamp, I personally learned a lot. Teacher were great professional and give us strong knowledges and competencies.

- Python programming
- Datamining
- Data analysis
- Machine Learning Supervised and Non Supervised
- NLP
- Deep Learning
- Data Engineering & Big Data

Python | Pandas | SQL & NoSQL | SparkML | SpacyML | Docker | FastAPI & Flask | TensorFlow
DataViz : Dash Plotly | Streamlit

My journey with the Artefact School of Data was truly remarkable. Their integrated approach to data science and data engineering offered a well-rounded perspective, preparing me for real-world challenges. The emphasis on practicality meant I was equipped with job-ready skills right from the get-go, which led to me landing a data engineering role shortly after graduation. If you're aiming to dive deep into the realms of data science and engineering, the Artefact School of Data stands out as a premier choice. Their educational excellence is evident in the outcomes, and the career opportunities post-course are impressive.

VIVADATA is an excellent school: it offers very structured courses, various and rich exercises. Teachers are highly qualified and have very good educational methods. They answer our questions and assist us even after the bootcamp. I learnt a lot in a very short time: that was higher than my expectations.

It's a very interesting bootcamp on Data Science, Machine Learning. During the last session from 22 June to 28 August 2020, we covered the fundamental of data analysis and exploration before going in the Machine Learning techniques. The days are divided in two parts: the first a course of up to 2 hours and the second a bunch of exercices or case studies to work on.

Excellente école pour percer tous les secrets du machine learning, data engineering et deep learning ;)

I have attend the Sept-Dec 2019 session of Vivadata bootcamp. Vivadata bootcamp is a 10 week program covering python programming, data collection, data analysis, machine learning (supervized and unsupervized), NLP, data engineering and deep learning.
I have found the content of the classes to be of high quality: written courses, video courses, exercises and corrections are accessible on their platform and remain accessible after the bootcamp. The courses are dense, oriented towards practice (lots of exercises and projects) and the pace was strong from the beginning to the end (be motivated!).
The teachers and teachers assistants are knowledgeable and very available to support students whenever questions are coming up. I enjoyed the teaching style, the playful content and engaging projects that contributes to make the challenging experience fun as well.
The cohort is kept to a maximum of 15 fellows (not always the case in other bootcamps). I appreciated that Vivadata accepted fellows from diverse backgrounds and levels of education (I’ve seen other bootcamp only accessible to fellow holding a master or PhD which is in my opinion meant to inflate their employment rate after the bootcamp) as long they show they are serious and motivated by completing the preparatory work.
While all the resources are available for free online, I am glad that I joined a bootcamp because I don’t think I would have been able to learn so much by myself in such a short amount of time. Having the support of classmates and teachers to solve issues allowed me to avoid great frustrations met when you start coding and being part of a cohort was very motivating.
I am extremely satisfied with the Vivadata’s bootcamp and I would recommend this bootcamp to someone motivated (because it requires a strong commitment) who wants to learn a lot about python and data science in a short amount of time and has for short term plan to add data skills to his/her current job/domain or long term plan (because it will require more practice and studying) to become a data scientist.