How to train in Data Science and become one from scratch?
A Data Scientist can find a job in any industry, from retail sales to nuclear physics. That is why such a specialist is sometimes called a master of big data. Data Scientist works at the intersection of 3 areas of knowledge: programming, statistics and machine learning.
Learning Paths for Career Advancement
Data Scientist works with company data, analyses it, looks for potential dependencies, draws conclusions on this basis and, if necessary, builds visualisations. To solve such tasks, the specialist uses mathematical algorithms, development tools and special programmes. A Data Scientist understands how to build a forecast and helps to make the right decisions.
This specialist uses Data Science methods to process large amounts of information. He builds and tests models of data behaviour. This is how he finds patterns in them and predicts future values. For example, knowing everything about the demand for a product earlier, Data Scientist helps the company to make a forecast about sales in the near future. All models are built thanks to machine learning algorithms.
Usually Data Scientists become for the following reasons:
There is a desire to learn a promising and highly paid profession.
There is experience in a related industry, but you want to move to a new, more demanded direction. Data Scientists are often programmers, marketers, financiers and business analysts.
In professional activities or scientific research, it is necessary to apply innovative technologies: big data, neural networks, artificial intelligence.
To work in Data Science you need find best data science and ai courses for improving programming skills and knowledge of maths beyond the school curriculum.
Course Benefits and Features
Why choose online artificial intelligence and data science courses?
Classes are taught by experienced programmers and analysts who explain complex material, such as probability theory or mathematical analysis in an easy-to-understand way with examples.
Recordings of all lessons are stored in your personal account. You will not have gaps in your knowledge, because webinars can be watched repeatedly at any time. The videos will stay with you forever.
After each topic there is a practical task. The tasks gradually become more complex, and by the end of the course you will build a neural network or recommendation system. That is, you will have projects ready for your portfolio.
If you cannot cope with a question on your own, the tutor will help you. He will point out mistakes and give recommendations.
Many schools help with finding a job for free, and also invite students for internships, so you will have the opportunity to gain experience in a real project.
Excellent knowledge of maths, statistics, programming languages, English, as well as creativity, communication and critical thinking: employers are willing to pay more for specialists with this set of skills.
How to Enroll in Data Science and AI Courses?
Let's tell you in detail what steps you need to go through to become a Data Science specialist:
Study mathematics and linear algebra. If you have knowledge within the school curriculum, you can start with books that explain the basic concepts in simple language: derivative, differential, matrix and so on.
Any analytics uses mathematical statistics and probability theory - these are the next big topics you should familiarise yourself with.
Working in Data Science is impossible without knowledge of programming languages. For a beginner, Python is suitable - it is relatively simple, flexible and feature-rich.
The next step is to learn machine learning algorithms: "with a teacher", "without a teacher", "with reinforcement". You need to learn how to collect data for analysis and visualise it.
Having sorted out the theory, move on to practice. For example, you can look for an assistant position or an internship in large IT companies!
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