Data Science Courses

486 Courses

Complete Machine Learning and Data Science: Zero to Mastery

Complete Machine Learning and Data Science: Zero to Mastery Complete Machine Learning and Data Science: Zero to Mastery Learn Machine Learning (Artificial Intelligence), Python, Data Science, Data Analysis, Tensorflow, Pandas & more. All using the latest in AI! Categories: Artificial Intelligence Courses, Python Courses.

Pluralsight

Assessing Your Company’s AI Talent Needs

Assessing Your Company’s AI Talent Needs Assembling the right AI team is crucial for organizational success. This course will teach you how to assess your company’s AI talent needs, identify key roles, develop a hiring plan, and foster a culture of continuous learning and innovation. In today's rapidly evolving.

AWS Skill Builder

AWS SimuLearn: Set Up an ML Environment

AWS SimuLearn is an online learning experience that pairs generative AI-powered simulations with hands-on practice to help individuals learn how to translate business problems into technical solutions through the simulation of dialog between a customer and a technology professional. AWS SimuLearn: Set Up an ML Environment In this AWS SimuLearn assi.

LinkedIn Learning

Develop with Python for AI and Machine Learning

AWS Skill Builder

Exam Prep Official Pretest: AWS Certified Machine Learning Engineer - Associate (MLA-C01 - English)

Exam Prep Official Pretest: AWS Certified Machine Learning Engineer - Associate (MLA-C01 - English) The Exam Prep Official Pretest: AWS Certified Machine Learning Engineer - Associate (MLA-C01 - English) includes 65 questions and has a time limit of 130 minutes. This pretest aligns with the MLA-C01 version of the exam and exam guide. About AWS Ce.

AWS Skill Builder

Exam Prep Official Practice Question Set: AWS Certified Machine Learning Engineer - Associate (MLA-C01 - English)

Exam Prep Official Practice Question Set: AWS Certified Machine Learning Engineer - Associate (MLA-C01 - English) The Exam Prep Official Practice Question Set: AWS Certified Machine Learning Engineer - Associate (MLA-C01 - English) includes 20 questions. This question set aligns with the MLA-C01 version of the exam and exam guide. Official practi.

LinkedIn Learning

Ya Xu: How to Turn AI from a Buzz Word to a Business Tool

Ya Xu: How to Turn AI from a Buzz Word to a Business Tool | LinkedIn Learning Ya Xu: How to Turn AI from a Buzz Word to a Business Tool Explore the opportunities and challenges presented by AI with Ya Xu, the head of data and AI at LinkedIn. This LinkedIn Learning course delves into practical approaches to integrating AI.

PyTorch for Deep Learning

PyTorch for Deep Learning Learn PyTorch and become a proficient Deep Learning Engineer. This PyTorch course is a step-by-step guide designed to help you develop your own deep learning models. The curriculum includes essential topics such as Computer Vision, Neural Networks, and much more.

Coursera

Ciencia de Datos Aplicada al Marketing

Ciencia de Datos Aplicada al Marketing - Coursera Históricamente, las matemáticas nacieron por la necesidad de entender nuestro entorno y tomar decisiones. La ciencia de datos se enfoca en el procesamiento de datos: analizar, explorar e interpretar conjuntos de datos, proporcionando una visión completa del presente. La ciencia de datos no es e.

Coursera

Generative AI for Data Science with Copilot

Generative AI for Data Science with Copilot This course provides a comprehensive introduction to Generative AI in data science. You'll explore the foundational concepts of generative AI, including GANs, VAEs, and Transformers, and discover how Microsoft Copilot leverages these models to streamline data science workflows. You'll gain hands-on exp.

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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

Complete Machine Learning and Data Science: Zero to Mastery

Assessing Your Company’s AI Talent Needs

AWS SimuLearn: Set Up an ML Environment

Develop with Python for AI and Machine Learning

Exam Prep Official Pretest: AWS Certified Machine Learning Engineer - Associate (MLA-C01 - English)

Exam Prep Official Practice Question Set: AWS Certified Machine Learning Engineer - Associate (MLA-C01 - English)

Ya Xu: How to Turn AI from a Buzz Word to a Business Tool

PyTorch for Deep Learning

Ciencia de Datos Aplicada al Marketing

Generative AI for Data Science with Copilot

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?