0
Views
Profession Data Analyst - free course from Skillbox, training, Date: November 29, 2023.
Miscellaneous / / November 30, 2023
Russian Internet company in the field of online education, founded in 2016. The controlling stake in Skilbox LLC belongs to VK. The company is considered the leader in the Russian professional online training market. It is also a leader in training for jobs related to the digital economy and online advertising.
Skillbox is a Russian company that specializes in online education. Skillbox calls itself an online university for in-demand skills.
The educational programs of the service are focused on four main areas:
- design;
- programming;
- marketing;
- control.
On the platform you can gain knowledge on current topics and in-demand skills. All courses are aimed at practice: we monitor the relevance of the material and help with employment and internships.
The Skillbox educational platform was launched in 2016. The company was founded by Igor Koropov (1989-2020) and Dmitry Krutov. Later they were joined by Andrey Anishchenko and Sergey Popkov. The general director of the company since its founding has been Dmitry Krutov. Skillbox received the Runet Prize twice: in 2018 in the Education and Personnel category, and in 2019 in the Technology and Innovation category.
In February 2019 Mail. Ru Group acquired 3% of the company, then increased the stake to 10.33% in March, and finally to 60.33% in December of the same year. According to the Mail's annual report. Ru Group, a controlling stake in the company cost it 1.6 billion rubles.
In November 2019, RBC included the company in the rating of the 35 largest EdTech companies in Russia, placing Skillbox in 6th place. In 2020, in the ranking of the top 10 largest EdTech companies compiled by RBC, Skillbox moved to 2nd place.
In October 2020 Mail. Ru Group increased its stake in the company to 70%. In November 2020, the co-founder of the platform, Igor Koropov, died in Sochi.
Gain basic knowledge of mathematics to work with machine learning. You will understand what approximation, interpolation, functions, regressions, matrices and vectors are. Learn to work with mathematical entities in the SymPy Python library.
Fundamentals of statistics and probability theory
You will understand the principles of working with random variables and events. Become familiar with some types of distributions and statistical tests that are useful in constructing models and testing hypotheses.
Internship opportunity
Basic knowledge and skills are enough to get an internship - you can continue studying on the course and in the company at the same time.
Advanced level: immersion in data analytics and employment
The average completion time is 6 months.
Data Analyst. Junior
- You will learn basic data analysis techniques and learn how to draw analytical conclusions. You will learn how to build basic types of graphs and visualize data correctly. You will practice identifying trends from tabular data in Excel and making forecasts.
- You will learn how to identify problems in a company’s marketing and improve advertising effectiveness. In practice, learn how to collect full-fledged sales funnels in Power BI and prepare reports. You will understand how to track customers more effectively using lead attribution and call tracking.
- Learn to download data from databases using Python, write SQL queries, and correct errors in the collected material. You will learn how to build a clear dashboard and formulate conclusions about the work done. Learn to work with tools for processing Big Data: Hadoop, Hive, Spark. Conduct an analysis of data on the work of the company’s contact center.
- You will learn how to evaluate the market before launching a startup, and in practice you will go through all the stages of a product analyst’s work from surveys to evaluation and prioritization of features.
- You will learn how to organize work using Scrum and Kanban methods. Learn to collect and check requirements for inconsistencies and document them. You will learn how to plan work, assess project risks and present the results.
- You will analyze typical test tasks, receive recommendations on writing a resume and an idea of how to develop as an analyst.
Finding a Job Using the Career Center
- A career consultant will help you prepare for an interview at a partner company. You will understand common questions and learn to worry less during interviews.
- Write a cover letter and format your resume correctly.
- When you are ready to undergo an interview, a career consultant will organize a meeting with the employer.
- At the interview, you present the projects you worked on during the course, and your knowledge and skills will be useful for completing test tasks.
Expert level. Choosing a Specialization
The average completion time is up to a year.
Product analytics
You will process data, study user interaction with the product, and interpret the collected information. The results obtained will help solve business problems.
Marketing Analytics
You will learn how to set up web and end-to-end analytics, create sales funnels, and analyze user behavior on the site.
BI analytics
Learn to create data warehouses, design SQL databases, and work with tables at an advanced level. You will solve business problems using analytics, clean data, store it correctly and visualize it.
Bonus courses
Developer Career: Employment and Development
You will learn how to choose a suitable vacancy, prepare for an interview and negotiate with an employer. You will be able to quickly get a position that meets your expectations and skills.
Git version control system
Learn to version code changes, create and manage repositories, branches, and resolve version conflicts. Learn useful rules for working with Git.
English for IT specialists
Gain language skills that will help you pass an interview with a foreign company and communicate comfortably in mixed teams.
Final projects
After completing the first level, prepare an introductory project. At the end of the advanced level, present your final work in three areas of analytics and decide which data you are more interested in working with.
Introduction to Data Science
Consolidate your new knowledge on an individual project - you will go from loading data to implementing a model. Solve the problems of a data engineer, ML engineer and data analyst to decide on your specialization.
Data Analyst. Junior
- Product Analytics: analyze the results of A/B testing for a product and decide what needs to be developed first.
- Marketing Analytics: prepare data, calculate conversions and LTV. Draw conclusions about the effectiveness of advertising campaigns.
- BI Analytics: build a plan-fact. Create dashboards that will allow you to understand which departments have the greatest impact on company performance.
Advantages: amount of knowledge and teachers. Disadvantages: some modules were unclear, the variety of tasks First of all, I would like to express special gratitude to the testing teacher. She always analyzed each task in detail and gave feedback on all issues. You could say this is my second course at skillbox. The first was "Data Scientist". Analytics. First level". Supply of materials...
Completed the Data Analyst course. The overall impression of the courses is positive
Pros: It will be interesting. Disadvantages: Not all topics are covered by good lecturers. The course provides a general introduction to the data analyst profession. Many different areas are covered. It is unlikely that you can study 4 hours a week. It took me longer. You shouldn’t expect that everything will be chewed and put in your mouth - no. If you decide, please be patient, I immediately recommend high-quality...
The purpose of this course is to introduce students to the theory and practice of deep learning and neural networks in an interactive format. During the course you will be offered several practical tasks. The last assignment is the final practical project. Based on the results of the course, a certificate of completion will be issued, which provides benefits for admission to bachelor's and master's programs at the Faculty of Faculty of Physics and Technology of the Moscow Institute of Physics and Technology. The basic stream is intended for those who are taking their first steps in Data Science. A significant part of the course is devoted to the Python language, data analysis libraries and mathematics for Data Science. in the second half we will talk about the general theory of neural networks, as well as about neural networks in computer vision
The course introduces students to the basic concepts of Data Science. We will look at basic algorithms (linear models, decision trees, KNN, compositions), and analyze data preparation (cleaning, generation of new features and their selection). The knowledge gained will be enough to solve a wide range of problems.
Master the Kotlin programming language - learn to use the integrated development environment and create object-oriented applications.
Subscribe
YOU MIGHT ALSO LIKE
-
-
-
22/12/2019