25 of the Best Online Data Science or Data Analytics Courses (2023)

In this article you will find the best online Data Science or Data Analytics online courses, available on the main e-Learning platforms in the world. Courses of different levels, which will give you a certificate.
The Best Online Data Science or Data Analytics Courses

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The online courses of Data Science, data analysis or data analytics cover a type of need, which was born with the digital transformation of companies, a transformation that organizations from all business sectors, of all kinds, have been forced to implement. . Services, industries, banking, all.

But data science is not a need only present in large corporations, service multinationals or technology giants. Data analysis is a need that every company, regardless of its size, must satisfy. In this article you will find the most outstanding courses on this subject, available on the most important e-Learning platforms in the world. Courses of different levels of deepening and time of dedication. It will be a matter of personal interest or prior knowledge to decide which of them fits what you are looking for. However, these virtual courses in Data Science that we present here comply with being academically valuable and you have the possibility of obtaining a certificate, which can be a gateway, to draw attention to your resume.

What is Data Science

According to Wikipedia, data science is an interdisciplinary field that involves scientific methods, processes and systems to extract knowledge or a better understanding of data in its different forms, whether structured or unstructured, which is a continuation of some fields of data analysis such as statistics, data mining, machine learning, and predictive analytics.

Data science is also defined as "a concept for unifying statistics, data analysis, machine learning, and their related methods, in order to understand and analyze real phenomena", employing techniques and theories drawn from many fields within the context of mathematics, statistics, information science, and computer science.

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Turing Award winner Jim Gray envisioned data science as a "fourth paradigm" of science (empirical, theoretical, computational, and now data-driven), stating that "everything about science is changing because of to the impact of information technology and the data deluge".

In this new paradigm, researchers rely on systems and processes that are very different from those used in the past, such as models, equations, algorithms, as well as evaluation and interpretation of results.


According to Glasdoor a data scientist, as professionals or experts in this field are called, in the United States market has an average annual income (salary) of US$117.279, based on information from more than 18.000 professionals. According to Burning Glass, the average entry salary can be as high as $67.900.

One of the reasons why a professional in this field is so well paid is that their function transcends one area of ​​the company (Marketing, Sales, for example), and ends up being an essential element in the organization as a whole, since His job lies in being able to interpret what happens not only outside the company with customers, the market, etc. but in all the internal departments, compiling the information that can be obtained from each one, analyzing it, merging it, and connecting it, in ways that are not conventional, to find non-conventional information, which can generate commercial opportunities, new products and innovation and in general, improvements that keep the company current and competitive.

What kind of online Data Science courses to study?

Data scientists use their analytical, statistical, and programming skills to collect, analyze, and interpret large data sets. They then use this information to develop data-driven solutions to tough business challenges. Data scientists typically have a bachelor's degree in statistics, mathematics, computer science, or economics. Data scientists have a wide range of technical skills including: statistics and machine learning, coding languages ​​like Python, databases like SQL, machine learning and reporting technologies, algorithms.

Courses that focus on these topics will be essential for data scientists.

Find in this article, information on Online Data Science or Data analytics courses, on Python, data analysis, databases, SQL, Statistics, Data Visualization, Hadoop SPARK, algorithms, among others.
Virtual courses, MOOCs, and other types of advanced virtual studies such as Professional Certificates, Specialized Programs, Expertrack, Microcredentials, among other study formats developed by the main e-Learning platforms in the world.

From world-renowned platforms such as Coursera, edX, Future Learn, Udemy, Linkedin Learning, CFI, among others, find in this post, courses highly valued by thousands of previous students, which will help you make better decisions about which is the most suitable course for your objectives.

Where to study an online Data Science course?

Online courses in online data science can currently be taken in many places. Perhaps some of the platforms available on the web offer quality studies. However, at AulaPro we have made a selection of the platforms that we consider to be the most relevant worldwide for online studies.

Discover thousands of courses with Coursera Plus. Annual subscription now and for a short time at only USD $199! Click and find out how.

In this sense, the studies in this list are developed by prestigious universities, which occupy the first places in the international rankings, by technological companies of recognized world impact, by international experts of proven effectiveness as instructors, offered to the public through platforms with the most advanced technological developments, in terms of learning experience, or specialized platforms in the specific subject.

The courses have different levels of depth. From short courses that address a specific topic with a dedication time, which will not exceed 6 weeks, to robust study programs that a period of 6 to 10 months, can leave the student with a deep knowledge and with even the ability to give a turning point in his professional career.

In this article you will find data science or data analytics studies of:

  • Coursera
  • edX
  • FutureLearn
  • Udemy
  • LinkedIn Learning
  • CFI
  • edureka



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Category: Data Analysis -- Developed by: Google

Prepare for a new career in the high-growth field of data analytics—no experience or degree required. Get professional training designed by Google and have the opportunity to connect with the best employers. There are 337,400 US job openings in data analytics with an average entry-level salary of $67,900.

Data analytics is the collection, transformation, and organization of data to draw conclusions, make predictions, and drive informed decision-making.

Over 8 courses, gain in-demand skills that will prepare you for an entry-level job. You'll learn from Google employees whose grounding in data analysis served as a launching pad for their own careers. With less than 10 hours per week, you can complete the certificate in less than 6 months.

You'll prepare for jobs that include associate or junior data analyst, database administrator, and more. Upon completion of the certificate, you can apply directly with Google and over 130 US employers including Walmart, Best Buy, Astreya.

82% of Google Career Certificate graduates report a positive career outcome, such as a new job, a promotion, or a raise within 6 months.

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Category: Fourth Industrial Revolution -- Developed by: IBM

Este IBM Data Science Professional Certificate, has a strong emphasis on applied learning. Except for the first course, all other courses include a series of hands-on labs on the IBM Cloud that will give you practical skills with applicability to real jobs, including: Tools: Jupyter/JupyterLab, GitHub, R Studio, and Watson Studio Libraries: Pandas, NumPy , Matplotlib, Seaborn, Folium, ipython-sql, Scikit-learn, ScipPy, etc. Projects: Random Album Generator, Home Price Prediction, Best Classifier Model, Neighborhood Battle.

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Applied Learning Project

This Professional Certificate has a strong emphasis on applied learning. Except for the first course, all other courses include a series of hands-on labs on the IBM Cloud that will give you practical skills with applicability to real jobs, including:

Tools: Jupyter / JupyterLab, GitHub, R Studio and Watson Studio

Libraries: Pandas, NumPy, Matplotlib, Seaborn, Folium, ipython-sql, Scikit-learn, ScipPy, etc.

Projects: Random Album Generator, Predict Home Prices, Best Classifier Model, Neighborhood Battle.

In addition to earning a Coursera Professional Certificate, you'll also receive an iIBM digital badge that recognizes your competency in data science.

This online Data Science course is an in-depth study, made up of 10 courses, and the participation of more than 10 instructors, some with a doctorate level, and in general data scientists, with extensive experience in the field.

Category: Fourth Industrial Revolution -- Developed by: SAS

Through the SAS Visual Business Analytics Professional Certificate, you gain access to hands-on projects that are integrated into the coursework for each course. Examples of projects include visual analytics methodology, report design with SAS Visual Analytics Review, data restructuring for forecast review, and using parameters to create advanced review reports.

With this SAS Visual Business Analytics program, you'll learn how to access and manipulate data, analyze data with a variety of interactive reports and charts, and design and share dashboards to visualize your data. SAS Visual Analytics is a useful skill in a variety of careers, including on today's list of business needs in roles such as an analyst, researcher, statistician, or data scientist.

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Category: Fourth Industrial Revolution -- Developed by: CORPORATE FINANCE INSTITUTE cfi

A long-awaited Online Data Science Course

One of the certificates developed by the Corporate Finance Institute, which has raised higher expectations, given the high level with which the CFI has been developing its previous certificates focused on financial analysis.

This virtual certified program in Data Analysis has the advantage of combining Business Intelligence, which gives it a unique strategic approach in the current market of virtual Data Science courses.

Analyze data like a pro using all the most popular business intelligence tools

  • Save hours by automating data transformation
  • Combine data to create world-class visuals and dashboards
  • Analyze and predict events using complex data sets

This CFI Certificate is made up of a robust package of 16 online courses on Data Science and related topics, of great value in professional performance, with an estimated dedication of between 150 to 200 hours, equivalent to 4 to 6 months of studies. .

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Category: Data Science -- Developed by: Meta

Start your career as a database engineer. Develop job-ready skills for an in-demand career and earn a Meta credential. No degree or experience is required to get started.

Build job-ready skills by learning from the best

Get started in the in-demand field of database engineering with a Professional Certificate from Meta. Learn the skills you need to design, implement, and manage structured and unstructured data, and gain experience with key tools through hands-on projects.

Common Job Titles: database engineer, data engineer, data architect, database administrator, solution architect, machine learning engineer, software engineer, data platform engineer.

Upon completion, you'll gain access to the Meta Career Programs job board, a job search platform that connects you with more than 200 employers who have committed to finding talent through Meta's certification programs, as well as career resources. professional support to help you with your work. look for.

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Category: Data Science -- Powered by: LinkedIn Learning

Data science is driving a global revolution that touches everything from business automation to social interaction.

It is also one of the fastest growing and most rewarding careers, employing analysts and engineers around the world.

This course provides an accessible, non-technical overview of the field, covering data science vocabulary, skills, jobs, tools, and techniques.

Instructor Barton Poulson defines the relationships to other data-saturated fields, such as machine learning and artificial intelligence.

Review core practices: data collection and analysis, formulating rules for classification and decision making, and crafting actionable insights.

It also discusses ethics and responsibility and provides guidance for further information. In the end, you'll see how data science can help you make better decisions, gain deeper insights, and make your work more effective and efficient.

Take advantage of the free 30-day trial offered by the LinkedIn Learning platform to complete this course and earn your certificate of completion. 

You just have to click on the name of the course, to visit its page on LinkedIn Learning.

Category: Data Science -- Powered by: AWS

Start here to become an AWS Solutions Architect. Gain the skills and knowledge to design architectural solutions on AWS and prepare for your AWS Certified Solutions Architect – Associate exam.

This professional certificate provides the knowledge and skills you need to start building your career in cloud architecture and helps you prepare for the AWS Certified Solutions Architect – Associate exam. You'll start by learning key AWS services for compute, storage, database, networking, monitoring, and security, then dive into how to design architectural solutions, how to create and operate a data lake, and how to prepare for the certification exam.

The certification AWS Certified Solutions Architect – Associate demonstrates knowledge and skills in AWS technology across a wide range of AWS services. The certification focuses on designing cost and performance optimized solutions and demonstrating a strong understanding of the AWS Well-Architected Framework. This AWS certification is one of the highest paying IT certifications, according to the SkillSoft IT Skills and Salary report . According to Enterprise Strategy Group , surveyed AWS certification holders credited their certification with their higher income (74%), higher trust (87%), and higher influence among coworkers (79%).

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Category: Data Science -- Developed by: Microsoft

Launch your career in data science. Apply data science and machine learning to deploy and run machine learning workloads on Azure.

This professional certificate is intended for data scientists with existing knowledge of Python and machine learning frameworks such as Scikit-Learn, PyTorch, and Tensorflow, who want to build and operate machine learning solutions in the cloud. This Professional Certificate teaches students how to build end-to-end solutions on Microsoft Azure.

They will learn how to manage Azure resources for machine learning; run experiments and train models; implement and operationalize machine learning solutions; and implement responsible machine learning.

They will also learn how to use Azure Databricks to explore, prepare, and model data; and integrate Databricks machine learning processes with Azure Machine Learning. This program consists of 5 courses to help you prepare to take the DP-100 Exam: Design and Implement a Data Science Solution on Azure.

The certification exam is an opportunity to demonstrate knowledge and experience in managing cloud-scale machine learning solutions using Azure Machine Learning. This professional certificate teaches you how to leverage your existing knowledge of Python and machine learning to manage data ingestion and preparation, model training and deployment, and monitoring of machine learning solutions on Microsoft Azure.

Each course teaches you the concepts and skills that are measured on the exam. At the end of this program, you'll be ready to take the DP-100: Design and Implement a Data Science Solution on Azure.

Category: Data Science -- Developed by: Johns Hopkins University

Assemble a Dream Team, ask the right questions, and dodge mistakes that derail data science projects.

This Specialized Program consists of four intensive courses. In this, students will master what it takes to know, start, and lead a data science company. You'll even be able to take the course if you don't have a background in data science. You'll get a crash course in data science so you know the field and understand your role as a leader. You'll also learn how to recruit, assemble, assess, and stimulate your team with additional skill sets and roles.

You'll learn the structure of the data science pipeline, the goals of each stage, and how to keep your team on target at all times. By the end of our you will understand different practical skills that will keep you grounded and help you overcome the common challenges that often derail data science projects.

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Category: Fourth Industrial Revolution -- Developed by: MIT Massachusetts Institute of Technology

Master the fundamentals of data science, statistics, and machine learning.

Analyze big data and make data-driven predictions using probabilistic models and statistical inference.

identify and implement appropriate models and methodologies to extract meaningful information for decision making Develop and build machine learning algorithms to extract meaningful information from seemingly unstructured data; Learn popular unsupervised learning methods, including clustering methodologies and supervised methods such as deep neural networks.

Completing this MicroMasters program will prepare you for jobs such as: Data Scientist, Data Analyst, Business Intelligence Analyst, Systems Analyst, Data Engineer.

This MicroMasters in Statistics and Data Science program is comprised of four online courses and a virtually proctored exam that will provide you with the foundational knowledge essential to understanding the methods and tools used in data science.

and hands-on training in data analytics and machine learning.

All courses are taught by MIT faculty at a pace and level of rigor similar to that of a face-to-face course at MIT.

The estimated duration of this online Data Science course in Micromaster format is 10 to 12 months.

Category: Economics Administration Accounting and related -- Developed by: Yale University

In the age of analytics, transforming vast amounts of data into meaningful insights and customer value is essential to an effective data-driven business practice. Develop Data Analysis Skills and Experience Professionals who can combine fundamental data discussion and statistical analysis with more advanced use of spreadsheets and SQL can quickly advance in this growing field as a data or business analyst.

This microcredential has been created in collaboration with Tableau for professionals seeking to master key statistical concepts and techniques and harness the data analysis tools essential to the modern practice of data analysis. You'll develop basic quantitative data analysis skills to manage and analyze complex data sets with Excel and SQL, and learn to make business recommendations using analytical models, progressing from diagnostic analysis to predictive models.

This online course in Data Science in Microcredential format offers 15 UK academic credits at postgraduate level from Coventry University. You will also receive an electronic transcript from Coventry University. Find out how credits work and where you can use them at FutureLearn.

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Category: Data Science -- Powered by: LinkedIn Learning

Data analysts examine information using data analysis tools and help their teams develop business insights and strategies.

You'll need skills in math, statistics, communications, and working with tools designed to perform data analysis and visualization. Explore this high-demand career.

This robust study on data analysis is made up of 13 courses that, in an intuitive and staggered way, introduce the student to the qualities and knowledge that they must acquire as a professional to work as a data analyst in an entry-level position.

Learn the non-technical skills effective data scientists must cultivate to turn their first job into a successful lifelong career.

Unleash the power of your organization's data. Learn how to perform data analysis in Microsoft Excel.

Learn how anyone, in any industry, can speak the language of data analysis. Find out how to prepare data, explore it visually, and describe it using statistical methods.

This course covers fundamental data analysis skills such as thinking like an analyst, collecting actionable data, SQL queries, data cleansing, and more.

Get real-world insights into using predictive analytics and data mining to solve problems.

Get started with Power BI. Learn how to use this powerful set of business analytics tools to create and share visualizations with others in your organization.

Communicate complex ideas quickly and comprehensively with data visualization. Turn information into works of art and intrigue your audience.

Get the data you need for analysis and reporting by writing your own SQL code. Learn to write basic SQL queries, sort and filter data, and join results from different tables.

Learn how to manipulate data and create meaningful visualizations with R, the programming language that powers modern data science.

Learn how to detect, prevent, and fix errors to keep your data clean, with Python.

Take advantage of the free 30-day trial offered by the LinkedIn Learning platform to complete this course and earn your certificate of completion. 

You just have to click on the name of the course, to visit its page on LinkedIn Learning.

Category: Data Science -- Powered by: LinkedIn Learning

Whether you work in IT or just have an interest in getting into this exciting field, this learning path will help you build a career in data science. Learn about the fundamental stages of data science work, from statistics and systems engineering to data mining and machine learning.

Develop a strong basic understanding of statistics, which is necessary for any field related to data science.

Discover the many job specialization categories within data science.

Learn how to collect, explore, and communicate with data through graphs and statistics.

This virtual course in Data Science is a learning itinerary made up of 8 courses and a total of 7 instructors, and has an estimated duration of 16 hours according to the video content.

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Category: Computer Science -- Developed by: Udemy

Interested in the field of machine learning? Then this course is for you! This course has been designed by two professional data scientists so that we can share our knowledge and help you learn complex theories, algorithms, and coding libraries in an easy way.

We will guide you step by step in the world of machine learning.

With each tutorial, you'll develop new skills and improve your understanding of this challenging but lucrative subfield of data science.

This course is fun and exciting, but at the same time, we delve into machine learning.

It is structured as follows: Part 1 – Data Preprocessing Part 2 – Regression: Simple Linear Regression, Multiple Linear Regression, Polynomial Regression, SVR, Decision Tree Regression, Random Forest Regression Part 3 – Classification: Logistic Regression, K -NN, SVM, Kernel SVM, Naive Bayes, Decision Tree Classification, Random Forest Classification Part 4 – Clustering: K-Means, Hierarchical Clustering Part 5 – Association Rule Learning: Apriori, Eclat Part 6 – Learning by Reinforcement: Upper Confidence Limit, Thompson Sampling Part 7 – Natural Language Processing: Bag-of-Words Model Algorithms for NLP Part 8 – Deep Learning: Artificial Neural Networks, Convolutional Neural Networks Part 9 – Dimensionality Reduction: PCA, LDA, Core PC Part 10 – Model Selection and Strengthening: k-fold Cross Validation, Parameter Tuning, Grid Search, XGBoost Also, the cu rso is packed with practical exercises based on real-life examples.

This online data science course has been taken by more than 800.000 students, and was ranked number 5 in our special The 100 Best Udemy Courses of All Time.

Category: Fourth Industrial Revolution -- Developed by: CloudSwyft Global Systems, Inc. Accredited by Microsoft

The basics of data science in Microsoft Azure using Python programming. This professional ExpertTrack is designed for students and working professionals who aspire to start their careers in analytics, data science, and machine learning.

It is most suitable for those looking to become IT professionals, data scientists, engineers and analysts, professors and statistics professionals, and generally those who are interested in learning more about data science.

Python provides great functionality for people who routinely deal with mathematical, statistical, and scientific functions as part of their job. It has become incredibly popular within data science in recent years as the code takes less time to develop than other programming languages, speeding up the development process and delivering more efficiency across all departments.

This virtual course in ExpertTrack Data Science offers you a change to familiarize yourself with the language and take the next steps to use it with confidence in a professional context. Explore Microsoft Azure Throughout this ExpertTrack, you will begin to understand cloud computing services and support services in Microsoft Azure, and how they relate to data science projects.

This Experttrack is made up of 5 courses that complete an approximate 15-week dedication.

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Category: Data Science -- Developed by: Monash University

In this course, the fundamental techniques used by professionals in the field of data science will be presented. You will learn the workflow of data analysis, data discussion, and data plotting, which lay the groundwork for more advanced techniques such as statistical modeling, regression and decision trees, sentiment analysis, and working with big data.

Being able to work effectively with a variety of data types and sources and then telling a story that informs decision making is crucial. In this course, you'll have the opportunity to hone your data science skills alongside other students as you do hands-on programming exercises that reflect scenarios from the world around us.

This course is offered jointly by the Monash Business School and the Faculty of Information Technology. Students who successfully complete the course and meet the Monash entry criteria can be awarded one unit or six credit points of academic credit towards a relevant Monash MSc in Business Analytics or IT.


Category: Fourth Industrial Revolution -- Developed by: Google

This virtual data science program provides you with the skills you need to advance your data engineering career and recommends training to support your preparation for the industry-recognized Google Cloud Professional Data Engineer certification.

Through a combination of presentations, demos, and labs, you'll enable data-driven decision making by collecting, transforming, and publishing data, and gain real-world experience through a series of hands-on projects using Qwiklabs.

You'll also have the opportunity to practice key job skills, including designing, building, and running data processing systems; and put machine learning models to work.
Upon successful completion of this program, you will earn a certificate of completion to share with your professional network and potential employers.

This Professional Certificate is made up of 5 courses that have an estimated duration of 4 months.

Category: Fourth Industrial Revolution -- Developed by: Tecnológico de Monterrey

This Professional Certification program will allow you to learn how applied data science will enable better decision-making for an organization.

If it is the first time that you handle data or you are only familiar with the use of Excel, this program will help you learn more about data analysis so that decision-making based on large volumes of information is the best.

You don't need to be a data scientist to master data science and data processing, due to artificial intelligence, machine learning, deep learning and digital transformation. more and more it is necessary to solve problems based on data extraction, to make the best decisions, for example the human resources department, marketing or a programmer who usually handle large amounts of data, can benefit from data processing for successful decision making and process improvement.

This Professional Certificate in Data Science is made up of 3 courses and has an estimated duration of 3 months.

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Category: Data Science -- Developed by: University of California Berkeley

This course will give you a new perspective to explore the topics and problems that interest you.

Among others, Berkeley's online data science program has been endorsed by Google's vice president of education and Microsoft's corporate vice president of cloud AI.

The program is based on Data 8, UC Berkeley's fastest growing class, which is taken by more than 3300 students each year as they begin their data science journey.

Data 8 is recognized among institutions as the preeminent introductory data science course that has helped place UC Berkeley at the forefront of democratizing data science for all.

Top-ranked universities around the world, such as Yale, Cornell, and NYU, have followed Berkeley's lead by creating their own versions of UC Berkeley's groundbreaking data science course.

Through this professional certificate, students from around the world can now take UC Berkeley's most popular course.

This course is accessible to students who have not previously taken statistics or computer science courses.


Category: Fourth Industrial Revolution -- Developed by: IBM

This Professional Certificate does not require any prior skills in programming or statistics, and is suitable for students with or without university degrees. Basic computer skills, high school math, comfort working with numbers, a willingness to learn, and a desire to enrich your profile with valuable skills are all you need to get started.

Upon successful completion of this program, you will have analyzed real-world data sets, created interactive dashboards, and presented reports to share your findings, giving you the confidence and portfolio to begin a career as an Associate or Junior Data Analyst. It will also create the foundation for other data disciplines, such as data science or data engineering.

Jumpstart your career as a data analyst by learning the basics of data analysis and gaining practical skills. You'll work with a variety of data sources, project scenarios, and data analysis tools, including Excel, SQL, Python, Jupyter Notebooks, and Cognos Analytics, gaining hands-on experience with data manipulation and the application of analytical techniques.

Category: Data Science -- Developed by: Corporate Finance Institute CFI

Data Science Fundamentals is a preparatory course for CFI's BIDA™ program

the next show Business Intelligence & Data Analyst (BIDA)™ of CFI will cover all the basic, intermediate and advanced topics on business intelligence and data analysis. This program will teach you the quantitative methods used in the finance industry and capital markets. It is ideal for students who want to learn how to analyze complex data.

Common career paths for students taking the BIDA™ program are business intelligence, asset management, data analyst, quantitative analyst, and other financial careers.

Students can sign up for updates and reserve a place in the Business Intelligence & Data Analyst (BIDA)™ program.

Category: Data Science -- Developed by: edureka!

This Tableau online training course is for anyone who works with data regardless of their technical or analytical background. Users can create and distribute shareable, interactive dashboards that represent large volumes of data in easily readable graphs and charts. Tableau dedureka training is designed to help you prepare for the Tableau Desktop Certified Associate certification exam by giving you enriching hands-on training in various Tableau tools. This Tableau certification training is a springboard for your Business Intelligence journey. Throughout this course, you will have the opportunity to work on various Tableau projects.

Discover new ways to analyze data, through several features built into Tableau. Create custom dynamic visualizations through parameters. Build interactive dashboards using actions. Explore good design practices for dashboards. Learn how to publish and share dashboards and manage permissions for your published data. Get extensive hands-on experience on various tips and tricks with Tableau.

Category: Data Science -- Powered by: LinkedIn Learning

There is a growing need for data scientists and analysts to understand relational data stores.

Organizations have long used SQL databases to store transactional data as well as data related to business intelligence.

If you need to work with SQL databases, this course is designed to help you learn how to perform common data science tasks, including searching, exploring, and extracting within relational databases.

The course begins with a brief overview of SQL.

Then, the top five topics a data scientist should understand when working with relational databases: basic statistics in SQL, data preparation in SQL, advanced filtering and data aggregation, window functions, and data preparation for use with SQL. Analysis tools.

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Category: Data Science -- Developed by: New York University

This program will teach you basic computer science skills in programming and data structures.

Understanding how programming works is essential in many technical disciplines, such as information technology, software engineering, cybersecurity, and computer science.

Courses use the C++ programming languages ​​to establish a strong foundation in programming and data structures for students.

Students gain valuable hands-on experience programming solutions to problems in the labs.

In the labs, students will practice their basic programming skills as well as develop many advanced data structures including hash tables, sort and search algorithms, binary trees, AVL trees, graph algorithms, and many more advanced computer science topics.


Category: Probability and Statistics -- Developed by: Duke University

In this specialization, you will learn to analyze and visualize data in R and create reproducible data analysis reports, demonstrate a conceptual understanding of the unified nature of statistical inference, perform Bayesian and frequent statistical modeling and inference to understand natural phenomena and make data decisions. , communicate statistical results correctly, effectively, and in context without relying on statistical jargon, critique data-driven claims and data-driven evaluated decisions, and discuss and visualize data with R packages for data analysis.

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