Coursera

Introduction to data analysis (Coursera)

Offered by Saint Petersburg State University,

With this course, you will begin to take the first steps in the world of data analysis. You will see in detail the main concepts and processes that make up this discipline. The main goal of the course is acquisition of knowledge about the mathematical and statistical basics underlying the main ideas and approaches used in data science. This is achieved through setting and solving typical tasks, which a researcher in the field of data science can face in his work. You will get practical skills in working with data analysis tools used in different spheres of human activity.

Class Deals by MOOC List - Click here and see Coursera's Active Discounts, Deals, and Promo Codes.

You will be acquainted with the main tasks, methods and basic algorithms, as well as with the spheres of their practical applications. You will know how applied problems of data processing and analysis are being solved. You will be acquainted with the main concepts of artificial neural networks and the ways they are being trained.

Syllabus

WEEK 1: Data and Big Data Analysis: Approaches, Functions and Software Tools
WEEK 2: Basic Characteristics of Data. Distributions, Statistics and Regressions
WEEK 3: Clustering and Dimensionality Reduction
WEEK 4: Machine Learning and Artificial Neural Networks

Go to Class

MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Related Courses

Coursera

University of Illinois at Urbana-Champaign

Applying Data Analytics in Marketing (Coursera)

Management & Leadership Business

This course introduces students to the science of business analytics while casting a keen eye toward the artful use of numbers found in the digital space. The goal is to provide businesses and managers with the foundation needed to apply data analytics to real-world challenges they confront daily in their professional lives.

Jun 13th 2026

4 Weeks

Business Marketing Analytics

Coursera

IBM

Data Science Methodology (Coursera)

Statistics & Data Analysis Data Science

Despite the recent increase in computing power and access to data over the last couple of decades, our ability to use the data within the decision making process is either lost or not maximized at all too often, we don't have a solid understanding of the questions being asked and how to apply the data correctly to the problem at hand.

Jun 12th 2026

3 Weeks

Data Modeling Methodology Data Science

Coursera

University of Pennsylvania

Introduction to Spreadsheets and Models (Coursera)

Management & Leadership Business

The simple spreadsheet is one of the most powerful data analysis tools that exists, and it’s available to almost anyone. Major corporations and small businesses alike use spreadsheet models to determine where key measures of their success are now, and where they are likely to be in the future. But in order to get the most out of a spreadsheet, you have know how to use it. This course is designed to give you an introduction to basic spreadsheet tools and formulas so that you can begin harness the power of spreadsheets to map the data you have now and to predict the data you may have in the future.

Jun 8th 2026

4 Weeks

Business Models Spreadsheets

Coursera

ESSEC Business School

Foundations of strategic business analytics (Coursera)

Management & Leadership Business

Who is this course for? This course is designed for students, business analysts, and data scientists who want to apply statistical knowledge and techniques to business contexts. For example, it may be suited to experienced statisticians, analysts, engineers who want to move more into a business role. You will find this course exciting and rewarding if you already have a background in statistics, can use R or another programming language and are familiar with databases and data analysis techniques such as regression, classification, and clustering.

Jun 8th 2026

4 Weeks

Data Analysis Analytics Presentations

Coursera

University of California, Irvine

Effective Problem-Solving and Decision-Making (Coursera)

Business

Critical thinking – the application of scientific methods and logical reasoning to problems and decisions – is the foundation of effective problem solving and decision making. Critical thinking enables us to avoid common obstacles, test our beliefs and assumptions, and correct distortions in our thought processes. Gain confidence in assessing problems accurately, evaluating alternative solutions, and anticipating likely risks. Learn how to use analysis, synthesis, and positive inquiry to address individual and organizational problems and develop the critical thinking skills needed in today’s turbulent times. Using case studies and situations encountered by class members, explore successful models and proven methods that are readily transferable on-the-job.

Jun 8th 2026

4 Weeks

Data Analysis Decision Making Critical Thinking

Coursera

Stanford University

Probabilistic Graphical Models 1: Representation (Coursera)

Statistics & Data Analysis Data Science

Probabilistic graphical models (PGMs) are a rich framework for encoding probability distributions over complex domains: joint (multivariate) distributions over large numbers of random variables that interact with each other. These representations sit at the intersection of statistics and computer science, relying on concepts from probability theory, graph algorithms, machine learning, and more. They are the basis for the state-of-the-art methods in a wide variety of applications, such as medical diagnosis, image understanding, speech recognition, natural language processing, and many, many more. They are also a foundational tool in formulating many machine learning problems.

Jun 8th 2026

5-12 Weeks

MATLAB Octave Machine Learning

Coursera

DeepLearning.AI

Natural Language Processing in TensorFlow (Coursera)

Data Science

If you are a software developer who wants to build scalable AI-powered algorithms, you need to understand how to use the tools to build them. This Specialization will teach you best practices for using TensorFlow, a popular open-source framework for machine learning.

Jun 10th 2026

4 Weeks

Machine Learning TensorFlow RNN

Coursera

DeepLearning.AI

How Diffusion Models Work (Coursera)

Computer Science

In How Diffusion Models Work, you will gain a deep familiarity with the diffusion process and the models which carry it out. More than simply pulling in a pre-built model or using an API, this course will teach you to build a diffusion model from scratch.

Jun 9th 2026

1 Week

Artificial Neural Networks Diffusion Models

Coursera

University of California, San Diego,Higher School of Economics - HSE University

Advanced Algorithms and Complexity (Coursera)

CS: Software Engineering CS: Theory

You've learned the basic algorithms now and are ready to step into the area of more complex problems and algorithms to solve them. Advanced algorithms build upon basic ones and use new ideas. We will start with networks flows which are used in more typical applications such as optimal matchings, finding disjoint paths and flight scheduling as well as more surprising ones like image segmentation in computer vision.

Jun 8th 2026

5-12 Weeks

Algorithms Data Structures Machine Learning

Coursera

University of Illinois at Urbana-Champaign

Pattern Discovery in Data Mining (Coursera)

Statistics & Data Analysis Data Science

Learn the general concepts of data mining along with basic methodologies and applications. Then dive into one subfield in data mining: pattern discovery. Learn in-depth concepts, methods, and applications of pattern discovery in data mining. We will also introduce methods for data-driven phrase mining and some interesting applications of pattern discovery. This course provides you the opportunity to learn skills and content to practice and engage in scalable pattern discovery methods on massive transactional data, discuss pattern evaluation measures, and study methods for mining diverse kinds of patterns, sequential patterns, and sub-graph patterns.

Jun 8th 2026

4 Weeks

Algorithms Data Mining Data Analysis

Coursera

University of Virginia

Marketing Analytics (Coursera)

Marketing & Communication Business

Organizations large and small are inundated with data about consumer choices. But that wealth of information does not always translate into better decisions. Knowing how to interpret data is the challenge -- and marketers in particular are increasingly expected to use analytics to inform and justify their decisions. Marketing analytics enables marketers to measure, manage and analyze marketing performance to maximize its effectiveness and optimize return on investment (ROI). Beyond the obvious sales and lead generation applications, marketing analytics can offer profound insights into customer preferences and trends, which can be further utilized for future marketing and business decisions.

Jun 8th 2026

5-12 Weeks

Marketing Regression Data Analysis

Coursera

Northwestern University

Leadership Through Marketing (Coursera)

Management & Leadership

The success of every organization depends on attracting and retaining customers. Although the marketing concepts for doing so are well established, digital technology has empowered customers, while producing massive amounts of data, revolutionizing the processes through which organizations attract and retain customers. In this course, students will learn how to identify new opportunities to create value for empowered consumers, develop strategies that yield an advantage over rivals, and develop the data science skills to lead more effectively, allocate resources, and to confront this very challenging environment with confidence.

Jun 14th 2026

4 Weeks

Marketing Strategy Leadership