Coursera Platform
General information about the platform
General information about the platform
Coursera is an online learning platform that provides a wide range of courses for anyone to learn at their own pace. The platform was first launched in 2012 and since then it has become the global leader in online learning courses with over 7,000 courses available. Coursera collaborates with top universities and experts to create high-quality courses that feature interactive content and peer-reviewed assignments. Besides, one can enhance their learning experience by participating in community discussion forums and live events.
Purpose and objective
Coursera was founded with a vision to make education more affordable as compared to traditional methods and accessible to everyone from anywhere. The platform offers a wide variety of courses, professional certificates, and degrees from top universities and organizations worldwide.
Benefits for applicants
- Many courses on Coursera are designed to equip learners with the skills needed in the job market.
- Accessible from anywhere from a computer/smartphone/tablet as long as there is an internet connection.
- Learning at own pace and own schedule.
- Courses for various levels of topics.
- Course completion certification
- High quality content of courses developed by professionals.
- Possibility to access course materials and complete courses free of charge.
Costs
Coursera offers a 7-day free trial that grants access to all courses. After the end of the free trial, you can select your subscription plan:
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Application process
To start the learning journey in Coursera, creating a personal profile is necessary, which can be done on the sign-up page. You can use your email, Google or Facebook account to create a profile.
After the signing up process, you can start your free 7-day trial.
To explore and find relevant courses for you, search in the taskbar for the exact topic of interest or start exploring the available courses from the Explore bar (see picture below).
you want to browse from all available courses go to the Browse all page.
At the top right corner of the Coursera main page, you can access information about courses that you have enrolled in through My Courses, edit your profile and information about yourself on the Coursera page through Profile, see all the purchases and subscriptions through My Purchases, edit and update information about your account details and preferences through Settings, check information about enrolled courses, specialisations and degrees through Updates, see all your successfully finished learning paths through Accomplishments, use Coursera help centre to find or ask any relevant question.
In the following sections, you can find information about the learning courses that are best rated and most popular among topics of Artificial Intelligence, data and business analysis, programming languages, business process automation, big data and big data analysis, online marketing tools, and website creation.
Artificial Intelligence and Machine Learning
AI for Business Course
About the course
AI For Business course developed by one of the top Universities of the USA, the University of Pennsylvania will introduce participants to possibilities that AI offer to support businesses from various aspects.
Required experience level and benefits of the course
The course is for beginners with little to no experience who want to learn AI, machine learning and big data fundamentals, and how to apply them to support your business.
By the end of this course, you will have an understanding of ethical AI, and the relationship between data analytics, AI and ML. More specifically, you will understand how to use AI, ML and data analytics for marketing, Finance, People management, and governance.
Brief content of the course
The course is divided into 4 courses:
- AI Fundamentals for Non-Data Scientists.
- AI Applications in Marketing and Finance.
- AI Applications in People Management.
- AI Strategy and Governance.
Duration of the course
The course is estimated to take 10 hours per week for a month to complete.
Machine Learning Course
About the course
The Machine Learning course is an online program developed by Standford University together with DeepLearning.Ai that teaches the basics of machine learning and how to use it in real-world AI applications.
Required experience level and benefits of the course
The course is for beginners who know basic level coding (for loops, functions, if/else statements) & high school-level math (arithmetic, algebra).
After completion of the course, you will be able to build ML models, apply unsupervised learning techniques for your model, build neural networks, and more.
Brief content of the course
The course is divided into 3 course series:
- Supervised Machine Learning: Regression and Classification.
- Advanced Learning Algorithms.
- Unsupervised Learning, Recommenders, Reinforcement Learning.
Duration of the course
The course is estimated to take 10 hours per week for two months to complete.
Natural Language Processing Course
About the course
Natural Language Processing course is designed to give participants information and practical tasks to learn about the subcategory of AI, Natural Language Processing (NLP). This technology is critical for effectively analysing massive quantities of unstructured, text-heavy data, and is one of the most widely applied areas of machine learning.
Required experience level and benefits of the course
This is an intermediate-level course for those who have a working knowledge of machine learning, intermediate Python experience including DL frameworks & proficiency in calculus, linear algebra, & statistics.
After course completion you will be able to:
- Use logistic regression, naïve Bayes, word veg, hidden Markov models, and word embeddings to autocorrect misspelt words, autocomplete partial sentences, and identify part-of-speech tags for words.
- Use dense and recurrent neural networks, LSTMs, GRUs, and Siamese networks in TensorFlow and Trax to perform advanced sentiment analysis, text generation, named entity recognition, and to identify duplicate questions.
- Use encoder-decoder, causal, and self-attention to perform advanced machine translation of complete sentences, text summarization, question-answering, and to build chatbots. Learn T5, BERT, transformer, reformer, and more.
Brief content of the course
The course is divided into 4 courses:
- Natural Language Processing with Classification and Vector Spaces.
- Natural Language Processing with Probabilistic Models.
- Natural Language Processing with Sequence Models.
- Natural Language Processing with Attention Models.
Duration of the course
It is estimated that the course takes 3 months at 10 hours per week of practice and learning to complete.
Machine Learning Engineering for Production (MLOps) course
About the course
Machine Learning Engineering for Production (MLOps) course is for those who want to become machine learning experts and be able to conceptualize, build, and maintain integrated systems that continuously operate in production.
Required experience level and benefits of the course
This is an advanced-level course, and it is recommended to have knowledge in AI/ deep learning, intermediate Python skills, and experience with any deep learning framework (PyTorch, Keras, or TensorFlow).
After completion of the course, you will be able to:
- Design an ML production system end-to-end: project scoping, data needs, modeling strategies, and deployment requirements.
- Establish a model baseline, address concept drift, and prototype how to develop, deploy, and continuously improve a production ML application.
- Build data pipelines by gathering, cleaning, and validating datasets.
- Implement feature engineering, transformation, and selection with TensorFlow Extended.
- Establish data lifecycle by leveraging data lineage and provenance metadata tools and follow data evolution with enterprise data schemas.
- Apply techniques to manage modelling resources and best serve offline/online inference requests.
- Use analytics to address model fairness, and explainability issues, and mitigate bottlenecks.
- Deliver deployment pipelines for model serving that require different infrastructures.
- Apply best practices and progressive delivery techniques to maintain a continuously operating production system.
Brief content of the course
The course is divided into 4 courses:
- Introduction to Machine Learning in Production.
- Machine Learning Data Lifecycle in Production.
- Machine Learning Modeling Pipelines in Production.
- Deploying Machine Learning Models in Production.
Duration of the course
It is estimated that the course takes 2 months at 10 hours per week of practice and learning to complete.
Data Analysis and Visualization Tools
Data Analysis and Visualization Foundations Course
About the course
The Data Analysis and Visualization Foundations course is designed to provide participants with basic knowledge of Excel and Cognos applications. This course is designed for learners interested in starting a career in the field of Data or Business Analytics.
Required experience level and benefits of the course
This is a beginner-level course and prior experience in data analytics is not needed. The course will equip participants with the knowledge to explain the basic functionality of spreadsheets and utilize Excel to perform a variety of data analysis tasks, list various types of charts and plots and create them, describe the data ecosystem, and tasks a Data Analyst performs.
Brief content of the course
The course is divided into 4 courses:
- Introduction to Data Analytics.
- Excel Basics for Data Analysis.
- Data Visualization and Dashboards with Excel and Cognos.
- Assessment for Data Analysis and Visualization Foundations.
Duration of the course
To complete the course, it is estimated to take the learning of 10 hours a week for 1 month.
Business Statistics and Analysis Course
About the course
The Business Statistics and Analysis Course developed by Rice University is one of the best-rated courses among those that focus on beginner-level data and business analysis. The content and practical tasks facilitate a basic understanding of business data analysis tools and techniques.
Required experience level and benefits of the course
This course is for beginners with no experience in data analysis.
After completion of the course, you will have knowledge in essential spreadsheet functions, descriptive business data measures, data modelling, basic probability concepts, linear regression models and more.
Brief content of the course
The course is divided into 5 courses:
- Introduction to Data Analysis Using Excel.
- Basic Data Descriptors, Statistical Distributions, and Application to Business Decisions.
- Business Applications of Hypothesis Testing and Confidence Interval Estimation.
- Linear Regression for Business Statistics.
- Business Statistics and Analysis Capstone.
Duration of the course
To complete the course, you need to invest 10 hours a week for 3 months.
Data Analysis with R Course
About the course
The Data Analysis with R course developed by Duke University is for those who want to learn how to use R and RStudio, one of the most popular and powerful statistical and analytical programming languages. R programming language is designed to generate statistical calculations, analysis, and visualizations, though R use cases are numerous.
Required experience level and benefits of the course
This is a beginner-level course designed so that anyone with no prior experience and knowledge in data analysis with R can learn the fundamentals.
In this course, you will learn to:
- Analyse and visualize data in R and create reproducible data analysis reports.
- Demonstrate a conceptual understanding of the unified nature of statistical inference.
- Perform frequentist and Bayesian statistical inference and modelling to understand natural phenomena and make data-based decisions.
- Communicate statistical results correctly, effectively, and in context without relying on statistical jargon.
- Critique data-based claims and evaluate data-based decisions.
- Wrangle and visualize data with R packages for data analysis.
Brief content of the course
The course is divided into 3 courses:
- Introduction to Probability and Data with R.
- Inferential Statistics.
- Linear Regression and Modeling.
Duration of the course
To complete the course, you need to invest 10 hours a week for 3 months.
Programming Skills
Python for Everybody Course
What the specialization is about
The Python for Everybody course is the first step into understanding and being able to utilize the possibilities that Python programming language provides for analysing data.
Required experience level and benefits of the course
This course is for beginners with no prior experience in Python programming.
In the track, you will learn about data structures, networked application program interfaces, and databases. The theoretical learning part, combined with practical tasks will give you experience and a better understanding of how to design and create your applications for data retrieval, processing, and visualization.
Brief content of the course
The course is divided into 5 courses:
- Programming for Everybody( getting started with Python).
- Python Data Structures.
- Using Python to Access Web Data.
- Using Databases with Python.
- Capstone: Retrieving, Processing, and Visualizing Data with Python.
Duration of the course
To complete the course, you need to invest 10 hours a week for 2 months.
Coding for Everyone: C and C++
About the course
The Coding for Everyone: C and C++ course introduces participants to C and C++ which are two of the most widely used programming languages. C is one of the first programming languages designed for system programming, which is still relevant today and from whom many other languages are built. Understanding C and C++ can provide a solid foundation for learning other languages more easily.
Required experience level and benefits of the course
This course is beginner-level level intended for all programming enthusiasts, as well as beginners, computer and other scientists, and artificial intelligence enthusiasts seeking to develop their programming skills in the foundational languages of C and C++.
In the course, you will learn about algorithms and how to properly express them, as well as how to write and debug code in both languages.
Brief content of the course
The course is divided into 4 courses:
- C for Everyone: Programming Fundamentals.
- C for Everyone: Structured Programming.
- C++ For C Programmers, Part A.
- C++ For C Programmers, Part B.
Duration of the course
To complete the course, you need to invest 10 hours a week for 1 month.
Java Programming and Software Engineering Fundamentals Specialization
About the course
The Java Programming and Software Engineering Fundamentals course is a comprehensive learning programme that is valuable for those who want to build a career in software engineering or for those who want to learn core programming concepts to solve complex problems. Java is used for the development of web applications, mobile applications, enterprise applications, embedded systems and more.
Required experience level and benefits of the course
The course is for beginners and designed to first introduce participants to basic principles, therefore, no prior experience is required.
After completion of this course, you will have gained skills in:
- Software engineering.
- Java programming.
- Data structures.
- Computer programming.
- HTML.
- Debugging.
- JavaScript.
- Cascading Style Sheets(CSS).
- Software design.
Brief content of the course
The course is divided into 5 courses:
- Programming Foundations with JavaScript, HTML and CSS.
- Java Programming: Solving Problems with Software.
- Java Programming: Arrays, Lists, and Structured Data.
- Java Programming: Principles of Software Design.
- Java Programming: Build a Recommendation System.
Duration of the course
To complete the course, you need to invest 10 hours a week for 6 months.
Learn SQL Basics for Data Science course
About the course
The Learn SQL Basics for Data Science course is developed by the University of California, Davis, and is aimed at those who want to learn about databases. SQL stands for Structured Query Language which is a programming language used for collecting, managing, storing and utilizing structured data.
This course is beneficial for companies that on a daily basis receive extensive amounts of structured data and want to use it to their benefit.
Required experience level and benefits of the course
This is a beginner-level course intended for a learner with no previous coding experience seeking to develop SQL query fluency. In this course you will learn to:
- Use SQL commands to filter, sort, & summarize data; manipulate strings, dates, & numerical data from different sources for analysis.
- Assess and create datasets to solve your business questions and problems using SQL.
- Use the collaborative Databricks workspace and create an end-to-end pipeline that reads data, transforms it, and saves the result.
- Use programmes such as Apache Spark and methods like data wrangling, AB testing, Delta Lake and more.
Brief content of the course
The specialization is divided into 4 courses:
- SQL for Data Science.
- Data Wrangling, Analysis and AB Testing with SQL.
- Distributed Computing with Spark SQL.
- SQL for Data Science Capstone Project.
Duration of the course
To complete the course, you need to invest 10 hours a week for 2 months.
Automation for Business Processes
Implementing RPA with Cognitive Automation and Analytics Course
About the course
The Implementing RPA with Cognitive Automation and Analytics course is designed to introduce RPA, provide a foundation of the RPA lifecycle–from design to bot deployment–and implement RPA with cognitive automation and analytics. With RPA, companies can deploy software robots to automate repetitive tasks, improving business processes and outcomes. When used in combination with cognitive automation and automation analytics, RPA can help transform the nature of work, adopting the model of a Digital Workforce for organizations.
Required experience level and benefits of the course
Experienced and novice users and developers of RPA will all benefit from completing this course.
During the track, you will learn to design a project plan for RPA implementation, deploy cognitive bots and monitor their performance via the IQ Bot portal, develop & test bots in AAE Client and deploy & monitor them via the Web Control Room, generate operational analytics on AAE Client and business analytics on Bot Insight.
Brief content of the course
The course consists of 4 courses:
- RPA Lifecycle: Introduction, Discovery and Design.
- RPA Lifecycle: Development and Testing.
- RPA Lifecycle: Deployment and Maintenance.
- Cognitive Solutions and RPA Analytics.
Duration of the course
The course should take approximately 1 month at 10 hours a week to complete.
Robotic Process Automation (RPA) Course
About the course
The Robotic Process Automation (RPA) course offers comprehensive knowledge and professional-level skills focused on developing and deploying software robots.
Required experience level and benefits of the course
This is a beginner-level course in the field of robotic processes, but it is recommended to have basic programming skills.
After course completion, you will have learned the basic concepts of Robotic Process Automation, how to independently design and create automation for business processes, and UiPath Platform configurations.
Brief content of the course
The course consists of 6 courses:
- RPA Basics and Introduction to UiPath.
- Data Manipulation in RPA.
- UI Automation and Selectors.
- Control Flow in RPA.
- Automation Techniques in RPA.
- UiPath Orchestrator and Capstone Projects
Duration of the specialization
The course should take approximately 1 month at 10 hours per week to complete.
Automation for Business Course
About the course
The Automation for Business is a short course that gives theoretical knowledge and skills to harness the transformative power of automation in today’s business environment.
Required experience level and benefits of the course
This is a beginner-level course with no prior automation experience is required, however, a general understanding of business operations and technology concepts will be beneficial.
Brief content of the course
In the course, you will learn fundamental automation concepts and terminologies, how to Analyze automation opportunities and strategies for implementation, Comprehend the benefits, challenges, and tools of business automation, and evaluate the impact of automation on business operations and the future of work.
Duration of the course
The course should take approximately 4 hours to complete.
Big Data and Big Data Analysis
Big Data Course
What the course is about
The Big Data course developed by UC SanDiego is a 6-course series that will teach you from basics about Big Data and Big Data tools. The data amount generated every day is immense and to manage huge amounts of data, typical data analysis tools fall short. Big data tools provide frameworks and methods to deal with large amounts of data and to get the best out of it.
Required experience level and benefits of the course
This track is for beginners who want to build an understanding of Big Data and Big data tools.
After completion of the track, you will know the basics of different tools of Big Data such as Apache Spark, Apache Hive, Apache Pig, and frameworks such as Hadoop MapReduce. This course will prepare you to ask the right questions about data, communicate effectively with data scientists, and do basic exploration of large, complex datasets.
Brief content of the course
The Specialization is divided into 6 courses:
- Introduction to Big Data.
- Big Data Modelling and Management Systems.
- Big Data Integration and Processing.
- Machine Learning with Big Data.
- Graph Analytics for Big Data.
- Big Data – Capstone Project.
Duration of the course
It is estimated to take 3 months at 10 hours per week to complete this course.
Modern Big Data Analysis with SQL Course
About the course
The Modern Big Data Analysis with SQL Specialization track is designed to show participants how to create modern distributed SQL engines for big data storage, as traditional relational databases fail to store large volumes of data. The track provides both theoretical and practical learning opportunities.
Required experience level and benefits of the course
The course is for beginners with no prior experience as well as for those who know SQL traditional relational databases but also want to gain skills for Big Data analysis. The track is for those who want to obtain skills in Big Data management with modern distributed SQL engines such as Apache Hive, Apache Impala, Apache Drill and Presto.
Brief content of the course
The course is divided into 3 courses:
- Foundations for Big Data Analysis with SQL.
- Analysing Big Data with SQL.
- Managing Big Data in Clusters and Cloud Storage.
Duration of the course
It is estimated to take 1 month at 10 hours per week to complete this course.
Software Architecture for Big Data course
About the course
Software Architecture for Big Data Specialization track is an advanced-level track for software engineers interested in the principles of building and architecting large software systems that use big data. The course series covers software architecture, transforming big data prototypes into tested production software, and building a production-ready distributed system. The instructors share their experiences to guide students throughout the courses.
Required experience level and benefits of the course
The course is an advanced level course and requires experience in software engineering or big data.
After completing the track, you will be able to test the first development of architecture, refactoring, continuous integration, and continuous delivery, create a performant, scalable distributed system that handles big data, and architect and create a big data or distributed system using rest collaboration, event collaboration, and batch processing.
Brief content of the course
The course is divided into 3 courses:
- Fundamentals of Software Architecture for Big Data.
- Software Architecture Patterns for Big Data.
- Applications of Software Architecture for Big Data.
Duration of the course
It is estimated to take 2 months at 10 hours per week to complete this course.
Online Marketing Tools
Digital Marketing Course
About the course
The Digital Marketing course track developed by the University of Illinois is designed to give participants fundamental knowledge about digital marketing and an overview of the latest digital marketing skills.
Required experience level and benefits of the course
This track is for those who have no experience in digital marketing and are keen on learning about digital marketing analytics, search engine optimization, social media marketing, and 3D Printing.
Upon finishing the Digital Marketing course, you will gain a better comprehension of the fundamental principles of the modern digital marketing industry. You will also obtain a fresh batch of stories, concepts, and tools that will allow you to create, distribute, promote, and price products and services digitally.
Brief content of the course
The track is divided into 7 courses:
- The Digital Marketing Revolution.
- Marketing in a Digital World.
- Digital Marketing Analytics in Theory.
- Digital Marketing Analytics in Practice.
- Digital Media and Marketing Principles.
- Digital Media and Marketing Strategies.
- Digital Marketing Capstone.
Duration of the course
It is estimated to take 4 months at 10 hours per week to complete this course.
Search Engine Optimization (SEO) Course
About the course
The Search Engine Optimization (SEO) Course by the University of California, Davis, offers to equip individuals with knowledge in search engines to improve company or product visibility on Google search and other search engines. The theoretical content provides information from fundamental concepts to advanced frameworks and tactics that can be used for achieving great product or service placement on search engines.
Required experience level and benefits of the course
This track is designed for beginners with little to no knowledge of search engines and their optimization, however, it is recommended to have some business experience.
After course completion you will be able to:
- Perform a competitive analysis on a webpage,
- Create influencer relationships and collaborations and analyse data to see which content gets the most shares,
- Develop a solid approach for achieving a productive and successful relationship with your client,
- Create a final report of your findings and recommendations for SEO and present your recommendations to your client.
Brief content of the course
The track is divided into 5 courses:
- Introduction to Google SEO.
- Google SEO Fundamentals.
- Optimizing a Website for Google Search.
- Advanced Content and Social Tactics to Optimize SEO.
- Google SEO Capstone Project.
Duration of the course
It is estimated to take 3 months at 10 hours per week to complete this course.
Introduction to Social Media Marketing Course
About the course
The Introduction to Social Media Marketing course developed by Meta, owner of Facebook, Instagram, and WhatsApp, has developed a short course for individuals planning on using one of the social media platforms for promotion of products and services. This course is part of the Meta Social Media Marketing Professional Certificate.
Required experience level and benefits of the course
The course is for individuals with no experience in social media or digital marketing.
After course completion, you will be able to:
- Understand the landscape of traditional, digital, and social media marketing,
- Create SMART goals, identify KPIs, and define your target audience and their customer journey,
- Understand how major social media platforms work,
- Choose the right social media platforms for your needs.
Brief content of the course
The course is divided into 5 modules:
- The Social Media Landscape,
- Social Media Platforms Overview,
- Goals and Planning for success,
- Understand Your Audience,
- Choose Your Social Media Channels.
Duration of the course
It is estimated to take 17 hours to complete this course.
Web Development
Web Design for Everybody: Basics of Web Development & Coding Course
About the course
The Web Design for Everybody: Basics of Web Development & Coding Course developed by the University of Michigan is a great starting point for those who want to build and design their website. In this track, you will learn to use tools such as JavaScript, Cascading Style Sheets (CSS), and HTML5 for website creation.
Required experience level and benefits of the course
The course is beginner-level and does not require prior knowledge of any of the tools used for WEB development and designing.
After completion of the track you will have basic knowledge in CSS, JavaScript and HTML5, and you will be able to write syntactically correct HTML and CSS code for websites, add interactive experience by using JavaScript, Use the Document Object Model (DOM) to modify pages, Apply a responsive design to enable the page to be viewed by various devices.
Brief content of the course
The track is divided into 5 courses:
- Introduction to HTML5.
- Introduction to CSS3.
- Interactivity with JavaScript.
- Advanced Styling with Responsive Design.
- Web Design for Everybody Capstone.
Duration of the course
It is estimated to take 2 months at 10 hours a week to complete this course.
Meta Front-End Developer Course
About the course
The Meta Front-End Developer Course is designed by software engineers at Meta, responsible for Facebook and Instagram website and mobile app design and user interface (UI). The combination of theoretical lectures and practical learning projects provides a valuable learning opportunity for everyone who wants to master developing and designing websites that people will interact with
Required experience level and benefits of the course
The course is beginner-level and does not require prior knowledge of Front-End Developer programming.
In this professional certificate track you will learn to:
- Create a responsive website using HTML to structure content.
- Use CSS to handle visual style.
- Use JavaScript to develop interactive experiences.
- Use React in relation to Javascript libraries and frameworks.
- Bootstrap CSS Framework to create webpages and work with GitHub repositories and version control.
Brief content of the course
The track is divided into 9 courses:
- Introduction to Front-End Development.
- Programming with JavaScript.
- Version Control.
- HTML and CSS in depth.
- React Basics.
- Advanced React.
- Principles of UX/UI Design.
- Front-End Developer Capstone.
- Coding Interview Preparation.
Duration of the course
It is estimated to take 7 months at 6 hours a week to complete this course.
Meta Back-End Developer Course
About the course
The Meta Back-End Developer Course teaches how to develop, maintain, and manage servers and databases while ensuring secure processes for webpages and mobile applications. This comprehensive learning opportunity utilises theoretical learning practices with practical tasks after each course.
Required experience level and benefits of the course
The course is beginner-level and does not require prior knowledge of Back-End Developer programming.
In this professional certificate track, you will learn to use programming systems including Python Syntax, Linux commands, Git, SQL, Version Control, Cloud Hosting, APIs, JSON, XML and more.
Brief content of the course
The track is divided into 9 courses:
- Introduction to Back-End Development.
- Programming in Python.
- Version Control.
- Introduction to Databases for Back-End Development.
- Django Web Framework.
- APIs.
- The Full Stack.
- Back-End Developer Capstone.
- Coding Interview Preparation.
Duration of the course
It is estimated to take 8 months at 6 hours a week to complete this course.
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