Data Science Courses

909 Courses

YouTube

Machine Learning in Finance - Lessons Learned

Explore ML's impact on finance, its current capabilities, and best practices for implementation. Learn to identify opportunities and avoid pitfalls in trading and banking applications.

YouTube

Free Video

32 minutes

On-Demand

University of Colorado Boulder

Data Visualization & Analytics in Tableau

Master data visualization with Tableau, learning to create effective visualizations, dashboards, and stories that transform complex data into clear insights, enhancing your analytics skills and marketability.

Coursera

Paid Course

Not Specified

On-Demand

YouTube

Asset Health and Predictive Maintenance with Databricks - Transforming Energy Series

Discover how Databricks Intelligence Platform enables asset health monitoring and predictive maintenance in the energy sector through industry trends, fundamentals, and practical demonstrations.

YouTube

Free Video

43 minutes

On-Demand

YouTube

Leveraging Data to Unlock Business Value

Discover how financial institutions and merchants use data to forge deeper customer connections, featuring Visa's strategies for enhancing interactions and managing risks to drive business growth.

YouTube

Free Video

38 minutes

On-Demand

YouTube

TIS Group's AI Journey: From Healthcare to Agriculture

Explore TIS.AI's innovative applications across healthcare and agriculture, including infant interaction platforms and vineyard solutions, while learning about the company's business foundations and future vision.

YouTube

Free Video

25 minutes

On-Demand

YouTube

Business Decision-Making in the Era of AI

Discover how AI revolutionizes business processes by streamlining data tasks, enabling direct AI interaction for insights, and democratizing data access for all organizational levels.

YouTube

Free Video

26 minutes

On-Demand

YouTube

Data Analysis in the Age of Data Democratization

Discover how to bridge the gap between non-technical users and data analysis, making data insights accessible to all while addressing challenges in data democratization within organizations.

YouTube

Free Video

22 minutes

On-Demand

YouTube

All About Biases in Artificial Intelligence

Explore biases in AI with Karen de Sousa Pesse, a STEM leader who examines data gaps and their impact while providing insights on building safer, more inclusive technologies for the future.

YouTube

Free Video

41 minutes

On-Demand

YouTube

LLMs - Application and Impact on Business

Explore how Large Language Models are transforming businesses with Sacha Khanin's keynote from DSC EUROPE 24, examining practical applications and strategic impacts.

YouTube

Free Video

40 minutes

On-Demand

YouTube

Data Science Guide: Using GenAI for Career Growth

Discover how GenAI is transforming data science careers with expert insights on essential tools, skills, and applications for both tech and non-tech professionals looking to transition into AI-driven roles.

YouTube

Free Video

56 minutes

On-Demand

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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!

Data Science Courses

Machine Learning in Finance - Lessons Learned

Data Visualization & Analytics in Tableau

Asset Health and Predictive Maintenance with Databricks - Transforming Energy Series

Leveraging Data to Unlock Business Value

TIS Group's AI Journey: From Healthcare to Agriculture

Business Decision-Making in the Era of AI

Data Analysis in the Age of Data Democratization

All About Biases in Artificial Intelligence

LLMs - Application and Impact on Business

Data Science Guide: Using GenAI for Career Growth

How to train in Data Science and become one from scratch?

Learning Paths for Career Advancement

Course Benefits and Features

How to Enroll in Data Science and AI Courses?