WANT TO BECOME AN ANALYST?
TRAINING WITH US == CAREERS IN IT
TRAINING WITH US == CAREERS IN IT
Learn at your own pace. Constant practice. Real tasks.
It will be very intensive, but the result is worth it.
It will be very intensive, but the result is worth it.
TRAINING FORMAT
WHO'S FITTING
ONLINE
FOR BEGINNERS
YOUR CV == IN 5 MONTHS
Jim
Matthews
Matthews
Data Analyst
I use Python to analyse data (pandas, numpy, matplotlib, seaborn), format results in Jupyter Notebook.
I use Tableau and Redash to visualise and create dashboards.
I work on collaborative projects via Jupyter Hub, use Git for teamwork. I have experience working on remote server via command line.
I know how to create complex queries in ClickHouse and PostgreSQL.
I can draw conclusions about the best product version based on the results of A/B testing.
I know the basic concepts of probability theory. I have experience in conducting statistical tests, price prediction based on linear models, as well as bootstrap analysis methods.
I understand how a product manager thinks and what value an analyst brings to the business, I know how to calculate key product metrics and apply them to analytical problems.
I use Tableau and Redash to visualise and create dashboards.
I work on collaborative projects via Jupyter Hub, use Git for teamwork. I have experience working on remote server via command line.
I know how to create complex queries in ClickHouse and PostgreSQL.
I can draw conclusions about the best product version based on the results of A/B testing.
I know the basic concepts of probability theory. I have experience in conducting statistical tests, price prediction based on linear models, as well as bootstrap analysis methods.
I understand how a product manager thinks and what value an analyst brings to the business, I know how to calculate key product metrics and apply them to analytical problems.
DESIRED SALARY FROM
$100,000 per annum
HOW TRAINING TAKES PLACE
COURSE DETAILS
The lecturers will talk about the course and its content. You will learn what is unique about each module, how much time you will need to master it and how it is all applied in leading IT companies.
WATCH THE LECTURES AND LEARN THE THEORY
- Interact with instructors in live seminars
- Study the materials at your own pace
- Study the materials at your own pace
CONSOLIDATE KNOWLEDGE IN SPECIALISED SIMULATORS
- Practise writing code in Python
- Create database queries
- Submit your solutions for review
- Learn from instructors and other students
- Create database queries
- Submit your solutions for review
- Learn from instructors and other students
WORK ON A REAL CLUSTER
- Practise in a live environment
- Work with Big Data on a cluster
- Analyse data in BI systems
- Work with Big Data on a cluster
- Analyse data in BI systems
ASK ANY SUPPORT QUESTIONS
- Discuss challenges and projects with market experts
- Your mentors will be data engineers from leading companies
- Your mentors will be data engineers from leading companies
TUITION FEE
Start mastering the data analytics profession, get access to remote server work and support from our instructors.
> Python
> Git
> SQL
> Probability theory
> Statistics
> A/B tests
> Visualisation
> Git
> SQL
> Probability theory
> Statistics
> A/B tests
> Visualisation
> Product Development
> Product analytics
> Airflow
> How to look for a job
> Final project
> Support from teachers
> Working on a remote server
> Product analytics
> Airflow
> How to look for a job
> Final project
> Support from teachers
> Working on a remote server
$500
REGISTRATION ON THE EDUCATION PLATFORM
To pay for the course, you need to register on our education platform with your first name, last name and email.
If you already have an account, you can use it.
If you already have an account, you can use it.
ASK A QUESTION
We will contact you and answer any questions you may have about
the course.
the course.
WHO THIS PROGRAMME IS FOR:
YOU ALREADY WORK IN ANALYTICS
CAREER START
You have no experience in data analysis but want to start a career in analytics. Our course assumes that you have at least a high school level of maths. We will teach you the rest!
You will be able to add in-demand tools such as Airflow, Git, Command line, Tableau to your arsenal of knowledge and increase your value on the labour market.
COURSE PROGRAMME ://
Let's lay the foundation: learn the basics of programming, get acquainted with libraries for data analysis, visualisation and working with the file system. It won't be easy, but cool analysts need to know these tools. From the first day we will start working on a remote server, everything is for real!
We will learn about the command line and the widely used version control tool, Git. We'll discuss basic commands, learn how to work with repositories, and see how Git allows you to bring together multiple developers and analysts to work on a single project.
We will learn the basics of SQL syntax. Using ClickHouse as an example, we will learn how to work with a database management system and connect to it using Python. We will start learning how to visualise our data correctly.
In this unit we will learn the basics of probability theory. Knowledge in this area is necessary for a deeper understanding of applied statistics.
We will learn how to plan A/B tests and test statistical hypotheses. The focus will be on the application of statistics to industry problems.
* In parallel with this block you will have an intermediate project
* In parallel with this block you will have an intermediate project
Practical A/B testing involves a lot of work with mathematical statistics. In the lectures we will consider the main problems of experiments and consolidate the knowledge gained through homework. 3 lessons, 2 homeworks. The block is held together with the partner experiment fest (2020).
An important skill of an analyst is to be able to properly present the results of their work in the form of an interactive dashboard. We will see what types of dashboards there are, learn how to select and design charts for different tasks, find out what should be emphasised in the layout, and practice gathering requirements for a dashboard from the customer. We will do all this in the Tableau BI system.
Form a product vision and a deeper understanding of the business and the product. We will learn how to find a common language with product managers and understand how data analysis can be used for business development. We will also look at how teams are organised in IT products.
We will understand what value analytics can bring and how to explain it to the business. We will learn how to identify the needs of product users and segment them, calculate unit economics, choose the right product metrics, and drive business growth through continuous hypothesis testing.
Earlier you have already learnt how you can solve tasks using python, sql and other tools. Sometimes there were tasks that needed to be done on a daily basis, such as keeping track of the stock price, calculating KPIs or checking the progress of your favourite team. To solve such tasks we have our own tools - both simple shedulers and complex process orchestration systems. Airflow is just such a system. Below we will get acquainted with how it works and how to use it to solve tasks
In the labour market, a competent presentation of your skills is sometimes as important as the skills themselves, and the inability to communicate properly can prevent even an experienced analyst from getting a job. In this block, we will discuss basic questions about finding a job in data analytics, use examples of different stages of job search, and ask questions of a professional recruiter from one of the largest IT companies.
You will try yourself in the role of an analyst performing a test assignment for a company. You will have access to a remote server and databases and practice solving problems that analysts face in their work. You will be presented with a choice of different analytical projects, during which you will be able to apply all the skills you have learnt during the course. You will write code, work with databases, automate routine tasks, look for insights in data and analyse the results of A/B tests. As with any large company, you'll go through a code review and get feedback using Git. The final project will allow you to consolidate your knowledge and will certainly make your CV more interesting for future employers.
ALUMNI FEEDBACK /
FAQ
People from different fields come into analytics: engineers, marketers, psychologists. Many people have to learn a new profession from scratch. If you are not sure that data analysis is for you yet, we recommend you to take the free demo - this way you will form a general idea of our course and understand whether this direction is suitable for you. By the way, the demo consists of Python lessons, which is the most difficult part. If you can cope with it, you will easily master the other modules as well.
To successfully complete the course, all you need to know is maths at a high school level. You will not need to know how to programme or write database queries. You can learn all this from scratch.
You can watch the lectures from any device, but you will need a computer or laptop to write code. There are no configuration or power requirements - we will provide all the necessary infrastructure to work on a remote server. At the start of training, you don't need to install any special software - you will only need a browser and standard applications for communication: Telegram, Discord, and Zoom.
On average, our students study 15 hours a week. This is enough time to be able to watch lectures and complete homework on time. However, the workload of all modules is different, and the first Python module is the most difficult. Therefore, we recommend that you allow more time for a good start - once you get used to the pace, it will be much easier.
We have organised the training in such a way that you can combine it with your work, study and personal life. You can study at any time and at your own pace - all lectures are pre-recorded and broken down into short videos (15-30 minutes on average), and there are soft two-week deadlines for homework.
There will be three lessons each week, which will be accessed gradually. The lessons will consist of video lectures, notes and practical assignments, which will take two weeks to complete. If you encounter difficulties during the course, you will be able to seek help from the support team. At the end of the course you will complete a final project and pass a real code-review.
ANY QUESTIONS?
Fill out the form, we will contact you, answer all your questions and tell you more about the course.
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