Practical introduction to
Python for Data Science

The perfect course for developers who want to enter the world of machine learning. I was very afraid of the huge amount of templates, rules that discourage me. It turned out that the course showed a simpler face of machine learning, there were a lot of analogies in the real world, which made it easier to understand many issues. I recommend it to anyone who wants to develop in this direction or find out if this is a good direction for the future.

This is a course in which knowledge stays in the memory for a long time. Participants leave the course with the knowledge, materials and skills to start their own project.

The course contains many practical examples, ready-made scenarios, theoretical explanations, and links to self-distributed materials. I recommend the course to people who want to start their adventure with machine learning and are looking for a place where they can learn practical skills.

The course met my expectations by 200% !!! Its biggest advantage is the fact that all the science is based on solving real problems using real data! During the course you can immediately see the practical application of the algorithms, which is a great motivation to learn and also opens your eyes to the possibilities of machine learning.

The organization of the course as a whole (video, webinar, backup) is also a big, big plus! You can really see that Vladimir is committed to the best possible knowledge transfer! I recommend it to everyone who is looking forward to it!

It is difficult to find materials that are mainly practice-based and contain structured topics in this area. The course allowed me to systematize my knowledge and indicate where I can go next. After taking the course, I can put ML into practice, but I know that this is only the tip of the iceberg.

In addition, I really liked the storytelling approach, anecdotes with such references to the real world. It gave us a better understanding of the problem at hand.

The course is the perfect introduction to the world of machine learning and deep learning for everyone. It not only gave me a better understanding of what both domains are, what algorithms should be used and why, but above all it gave me a solid foundation for further work. Vladimir is always there to help and tries to give help to everyone. The course community in Slack will also offer good advice and lend a helping hand. It's definitely worth participating in, and if someone has a bit more money, buy the higher package.

Extremely comprehensive and content-rich training based on practical tasks.

Well prepared environment and materials allow you to focus on learning the material, in addition, the participants create a useful community.

I recommend it to everyone, not just programmers.

A huge dose of practical knowledge in an accessible form. Endless examples and analogies from everyday life mean that understanding the material is effortless.

These 8 weeks of the course allowed me to understand what machine learning really is and what solving business problems would look like in practice. This course cannot be compared to any textbook or Coursera course.

What makes this course an incomparably better choice is its interactive nature (webinars, Slack discussions) and Vladimir's full participation. I can say with all responsibility that I have no regrets.

I recommend the course to people who want to see what machine learning and best practices related to solving problems using it look like in practice. They also want to learn the basics of Python and the rather large selection of machine learning libraries that are currently "on top".

How is Vladimir's machine learning course different? The course is prepared very robustly and thoughtfully. In addition to an accessible explanation of various classification and regression models, the course also focused on details important for applying ML in practice.

If you want to meet an interesting person who has experience in using machine learning in production and at the same time has an excellent ability to explain often complex methods in a clear way, I highly recommend the machine learning course led by Vladimir.

He promised 100% satisfaction with this course and delivered much more. I got the impression that Vladimir puts his whole heart into his work and, importantly, leaves no questions to the course participants, spending a lot of time talking to them and clarifying doubts.

An additional advantage of this course is the opportunity to exchange experiences and opinions on topics related to machine learning, both with Vladimir and with other course participants.

I highly recommend this course to all programmers, but not necessarily Python programmers, but also to anyone interested in data analysis.

In each module, after a short theoretical introduction, all concepts were "reworked" to interesting problems, thanks to which I gained new knowledge in practice, gradually mastering new topics.

After the first module, I was able to use the knowledge gained to work on my own project, which I am very satisfied with. My best investment in 2017 :)

A great move in form. Aimed at using machine learning as a means of adding value to businesses. Knowledge is imparted in a very accessible way.

Great introductory videos for each step of the course. The course has given me a great "fishing rod" to develop my own projects based on machine learning and neural networks.

I recommend the course to programmers who want to quickly learn the latest techniques related to machine learning and neural networks.

I also recommend it to people responsible for implementing technologies in small startups and large companies. You will definitely learn how to do it and what are the best practices in production. If you want to develop a startup implementing an idea using ML, after this course you will be able to do it, and maybe even partially implement it during the course!

An excellent course on machine learning, it covers a wide range of topics from the basics to more advanced topics. I have no doubt that the material covered in this course is just the tip of the iceberg, with each of the topics presented so clearly (with the help of practical exercises) that further development in the chosen subject should not be a problem.

I recommend the course to anyone interested in machine learning, not just programmers, although a solid Python foundation seems crucial to effectively handling individual modules.

The workshops helped me to systematize my knowledge and try to put into practice well-prepared typical tasks.

Thanks to the workshops I met other people interested in this topic, I was able to exchange knowledge and learn more about XGBoost.

The workshops are worth taking part in, they are held in a relaxed atmosphere, and Vladimir has a gift for translating complex things in an accessible way.

If you want to try your hand at machine learning or talk to others about your experiences, I recommend Vladimir's masterclasses.

I highly recommend DataWorkshop. It has been very valuable to me. Vladimir definitely has knowledge and experience in this field.

However, what makes this course special, in my opinion, is his approach to teaching:

→ Students first and foremost - speaking in a language tailored to the audience

→ Top-down approach - high level concept first, then the details

→ Clarity - Vladimir's ability to explain complex topics in simple words.

→ Examples and analogies from real life

Although I am a telecommunications engineer and not a certified programmer, after DataWorkshop I was able to successfully implement several machine learning models at work.

I recommend this course to anyone who wants to learn ML and AI quickly.

I went to the workshop to learn and systematize what I knew about machine learning so far. The most important thing for me was to familiarize myself with Kaggle and get practical skills, for example, how to use Jupyter Notebooks and write my algorithms in them. It is worth noting that Vladimir leads the workshop in such a way that you can easily keep up before you have no special training.

Thanks to clear instructions on how to prepare for the workshop, I created an Anaconda environment and installed basic Python packages for machine learning.

During the workshop, I learned which Python libraries are used in Data Science and what they are used for. So far I have spent a lot of time setting up the environment, a choice of Python version and libraries is supported. The workshops (as well as the preparation for the workshops) helped me get through this in a very short time.

Master classes are held in classrooms, with a nice atmosphere and teamwork. Vladimir runs a good school :) He starts with a small level of difficulty, gradually diversifies the examples and develops the main task. This encourages questions and discussions.

The workshop convinced me that it's worth exploring the field of data science, getting interested in Kaggle and importantly, unattainable if you dedicate your time to it. They motivated me to further my development and thus change my job :) I now work as a data engineer in the business intelligence department of General Electric.

I recommend it to anyone who is interested in data science and wants to practically work on a problem. If you like asking questions and looking for answers, I highly recommend it.

I recommend the workshops to anyone interested in the world. When I first appeared at the workshop, I had no idea about artificial intelligence, let alone its implementation in python.

Today, I can solve similar problems on my own "from production". During the workshops, I gained not only experience in implementing various algorithms, but also a lot of interesting facts about the world, because we worked with real data every time.

I have to admit that sometimes Vladimir introduced elements of competition between participants, which motivated us additionally. I would like to add that this is also a very good option for "networking", because you can meet interesting people among the participants.

DataWorkshop with Vladimir is a series of successful data science meetups.

Designed for beginner and intermediate data scientists who want to broaden their horizons with the help of brilliant cases shared by Vladimir.

The very friendly and informal atmosphere encourages the audience to actively participate in the workshops and even lead the meeting with their stories (for a few minutes, of course).

His broad and deep knowledge in artificial intelligence and machine learning allowed him to inspire the participants and teach them new tools and techniques.

It's hard to organize workshops well, especially for people with different technological backgrounds. But with DataWorkshop everything went smoothly, you just had to follow the instructions provided in advance.

Thank you very much :D

Vladmir explains complex machine learning (ML) models and algorithms in a very friendly, reliable and practical way. It covers state-of-the-art machine learning algorithms and practical methods of applying them.

Why participate in Data Workshop? High level of classes and interesting presentation of topics. I'm not currently using AI at work, but I have such plans for the near future.

I recommend Data Workshop to people who want to start their adventure with artificial intelligence and practical ways to use it.

I was fascinated by machine learning, and I was looking for different ways

to increase my knowledge and skills, and that's how I came across Vladimir's workshops.

Thanks to them I got better acquainted with Gradient Boosting methods, and it's great.

Results in practice, but not very well known. I've also been practicing and developing

other methods such as neural networks or hyperparameter tuning.

Workshops are a good opportunity to meet people who are really learning ML, the topic of

it's popular lately, a lot of people talk about it, but almost nobody does anything about it.

To people who want to learn ML, I recommend seminars as an important element.

learning process.

I have participated in all the previous workshops. It was (is) an unusual journey through machine learning. Vladimir presented challenging issues of feature design, visualization, cross-validation, gradient boosting or regularization in an accessible and interesting way.

A great advantage of the meetings are the Python source codes run during the sessions. They are well prepared and, in addition to presenting concepts, introduce applications of interesting libraries (e.g. xgboost, keras).

In addition to my knowledge of ML, I also gained practical knowledge of tools (python, jupiter notebook) that will be useful to me in my work.

I recommend Meetups with Vladimir to everyone who is interested in ML and BigData.

During the workshop I learned how to perform the whole process of machine learning, from data preparation through model training to its evaluation and use.

Vladimir explained related issues in an accessible way, often referring to real examples, including the value of machine learning for business.

The workshops improved my knowledge mainly in the area of practical use of popular libraries to solve real-world problems.