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12 Courses in Data Science, Machine Learning and Neural Networks!

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Data science and machine learning are victorious across the planet – now no one has any doubt that these areas are the future of technology. Fortunately, it is not too late to join a promising direction. We have collected 12 courses in data science, machine learning and neural networks for beginners and experienced developers who want to deepen their knowledge.

Profession “Data Scientist” from Scratch

  • Organizer: SkillFactory
  • Language: Russian
  • Where and when: online since April 29 (duration – 1 year)
  • Costs: 150 000 grate. (a discount of 50% applies until April 27th)

SkillFactory offers to specialize in a data scientist in one year: During this time, you will learn Python, classic machine learning, the secrets of working with neural networks, deep learning and data engineering. From the beginning of the program you have a personal mentor and internship opportunities.

12 Courses in Data Science, Machine Learning and Neural Networks!

Deep Learning

  • Organizer: “Neurology”
  • Language: Russian
  • Where and when: Full time and online from May 15th to July 1st, 2020 (duration – 2 months)
  • Costs: 27,000 rub.

An advanced course for data scientists, data engineers, programmers, and developers. The program will talk about tools to help deepen skills and go to the team to create middle-level data products.

12 Courses in Data Science, Machine Learning and Neural Networks!

Machine learning

  • Organizer: OTUS
  • Language: Russian
  • Where and when: online since May 28th (duration – 5 months, 4 academic hours per week)
  • Costs: 70,000 rub.

In this course, you will not only learn the theory of machine learning algorithms, but also acquire practical knowledge in dealing with data. Teachers will train machine learning to predict time series and end-to-end pipelines for working with data and to prepare for competitions at Kaggle.

Big Data Specialist

  • Organizer: Laboratory for new professions
  • Language: Russian
  • Where and when: September 29 – December 19, 2020 in the MegaFon office or remotely online (duration – 4 months)
  • Costs: 150 000 grate.

Program for experienced developers, analysts, and Junior DS. Together with industry professionals, students learn how to process data in pandas, create machine learning models, analyze text data, and use various algorithms from recommendation systems.

12 Courses in Data Science, Machine Learning and Neural Networks!

Demolition Courses in Data Science

  • Organizer: Johns Hopkins University and Coursera Platform
  • Language: English with Russian subtitles
  • Where and when: online at any time (duration – 1 week)
  • Costs: free

An introductory course for those who want to quickly understand big data and use it in a company. Students learn basic terms, find out what role data plays in business, and learn tools for working with large amounts of information.

12 Courses in Data Science, Machine Learning and Neural Networks!

Neural Networks

  • Organizer: Institute for Bioinformatics and Stepik Platform
  • Language: Russian
  • Where and when: online at any time (duration – 33 hours)
  • Costs: free

A free course for students and researchers of all disciplines as well as for pupils in special areas. The students master the theoretical basics of neural networks and learn to solve these problems in the field of data analysis.

12 Courses in Data Science, Machine Learning and Neural Networks!

Data Science

  • Organizer: Geekbrains
  • Language: Russian
  • Where and when: online since April 25 (duration – 18 months)
  • Costs: 162,000 rub.

Students are introduced to machine learning technologies and neural networks to solve real business problems. After training, you can try subjects like machine learning, artificial intelligence, neural networks, data analysis, and data science. Sufficient school knowledge for admission to the course.

12 Courses in Data Science, Machine Learning and Neural Networks!

Fundamentals of Machine Learning

  • Organizer: University of California San Diego
  • Language: English
  • Where and when: online since April 28th (duration – 10 weeks)
  • Costs: free

Machine learning in big data is a course for advanced learners who learn how to classify images, analyze many different types of data, and put this knowledge into practice. All programming tasks require knowledge of Python.

12 Courses in Data Science, Machine Learning and Neural Networks!

Data Science -IBM

  • Organizer: IBM
  • Language: English
  • Where and when: online at any time (duration – 12 months)
  • Costs: $ 369.90

The curriculum covers a wide range of data science topics: data visualization tools, Python, databases, SQL, data analysis, and machine learning. No knowledge of computer science or programming is required to participate in the program. After completing the course, participants will receive an IBM Data Science Professional certificate.

12 Courses in Data Science, Machine Learning and Neural Networks!

Master in Finance and Technology with three specializations in one program: Product Owner, Data Analytics, Data Scientist

  • Organizer: RANEPA and Sberbank
  • Language: Russian
  • Where and when: offline and online from September 1st (duration – 2 years)
  • Costs: free

In order to register for the program, you must pass the entrance tests.

Fintech 2020 was founded in 2016 and is a leading master in digital banking, digital product development and data analysis. As part of the program, the student learns programming languages ​​and machine learning, the IT-based products and services of the bank, and the environment.

12 Courses in Data Science, Machine Learning and Neural Networks!

Data Science Math Skills

  • Organizer: Duke University and Coursera Platform
  • Language: English
  • Where and when: online at any time (duration – 18 hours)
  • Costs: free

The course is dedicated to studying the basics of mathematics, on the basis of which data science is built. Students who have completed this program understand the meaning of the names, notations, and algebra rules that are required to continue studying more complex materials. The program is useful for those who want to master data analysis in Excel.

12 Courses in Data Science, Machine Learning and Neural Networks!

Complete Data Science Bootcamp

  • Organizer: Udemy
  • Language: English
  • Where and when: online at any time (duration – 28 hours)
  • Costs: 19 799 rub. (a discount of 93% applies until April 23)

The curriculum of the course covers a wide range of data science topics: understanding of the natural sciences, mathematics, statistics, Python, application of advanced statistical methods, data visualization, machine learning, deep learning. The program is suitable for beginners without relevant work experience.

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Science

What is the Difference Between Losers and Winners

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What is the Difference Between Losers and Winners

Self-development

What is the Difference Between Losers and Winners

Man is a social being, for his survival, he needs a group. Unsurprisingly, a large proportion of our instincts and programmed behaviors are geared toward building intragroup relationships — collaboration and competition for resources. There are three basic strategies for this interaction: take, give and exchange. More details – in this material, prepared according to the book “Find a Mentor“.

Three strategies



Find a mentor

Depending on the circumstances, we can use any of the three strategies, but, as a rule, each of us has one that we prefer.

“Exchangers” – these are those who act on the principle “I give, so that you give me too.” They are the majority in society. Their focus is justice.

“The takers” – focused on maximizing their own benefits in a relationship. The interests of others do not bother them.

Finally, there is also “Givers” – these people are focused on selfless help to others. Their focus is relationships.

What is the Difference Between Losers and Winners

What is the Difference Between Losers and Winners

Which of these strategies is more winning? Based on the research data, the following can be said. In the early stages, the takers are the most successful, while the givers are the outsiders.

As you move up, the picture changes to the opposite. There are almost no “takers” at the heights of success. But among those who have achieved outstanding results, there are unexpectedly many “giving”. The “exchangers” show stable average results at all levels.

People who are focused on their own benefit rarely reach the top. The reasons for this are obvious. A systematic disregard for the interests of others alienates those around them and increases hostility. In other words, within the framework of this strategy, each subsequent step repels friends and multiplies enemies. As a result, sooner or later, a person remains alone. It’s good if by that time he manages to reach the top.

But even so, success often looks like this: you are sitting in a tree, under which a pack of hungry wolves has gathered.

Another strategy of greatest interest is “give”. According to research conducted, most selfless and selfless altruists who are concerned about the welfare of others and are willing to help them to the detriment of their own interests are losers, which seems quite natural. On the other hand, it is the “givers” who achieve the greatest successes.

What is the Difference Between Losers and Winners

What is the Difference Between Losers and Winners

Key factor

Why? Is this a game of chance, or is there some factor that distinguishes successful givers from unsuccessful ones? Such a factor really exists. And this is your environment. Both are equally trying to help everyone and do not expect immediate rewards. Both those and others in response receive the sympathy and approval of others. Some of them seek to provide a reciprocal service – they are “exchangers”. Some take advantage of the value they receive without considering it necessary to give something in return – these are the “takers.”

The difference between losers and winners is what happens next.

The loser continues to help everyone equally. And here everything depends on the case – how many “takers” will be in his environment. If not enough, he will survive. If there is a lot, it will quickly lose all resources and opportunities for growth. The winner, on the other hand, knows how to identify the “takers” and remove them from his circle, so a network is gradually formed around him, which together brings him more than he put into its formation. From some point on, it becomes a key success factor. And the sooner he learns to do this, the higher his chances of achieving outstanding results.

Prepared according to the book “Find a Mentor“.

What is the Difference Between Losers and Winners

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