Most Popular Online Computer Courses

Python for Everybody Specialization

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Beginner Level
No prior experience required.

Approx. 8 months to complete

Learn to Program and Analyze Data with Python. Develop programs to gather, clean, analyze, and visualize data.

This Specialization builds on the success of the Python for Everybody course and will introduce fundamental programming concepts including data structures, networked application program interfaces, and databases, using the Python programming language. In the Capstone Project, you’ll use the technologies learned throughout the Specialization to design and create your own applications for data retrieval, processing, and visualization.

Python 3 Programming Specialization

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Beginner Level
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Approx. 7 months to complete

Become a Fluent Python Programmer. Learn the fundamentals and become an independent programmer.

This specialization teaches the fundamentals of programming in Python 3. We will begin at the beginning, with variables, conditionals, and loops, and get to some intermediate material like keyword parameters, list comprehensions, lambda expressions, and class inheritance.

You will have lots of opportunities to practice. You will also learn ways to reason about program execution, so that it is no longer mysterious and you are able to debug programs when they don’t work.

By the end of the specialization, you’ll be writing programs that query Internet APIs for data and extract useful information from them. And you’ll be able to learn to use new modules and APIs on your own by reading the documentation. That will give you a great launch toward being an independent Python programmer.

This specialization is a good next step for you if you have completed Python for Everybody but want a more in-depth treatment of Python fundamentals and more practice, so that you can proceed with confidence to specializations like Applied Data Science with Python.

But it is also appropriate as a first set of courses in Python if you are already familiar with some other programming language, or if you are up for the challenge of diving in head-first.

By the end of the second course, you will create a simple sentiment analyzer that counts the number of positive and negative words in tweets. In the third course, you will mash up two APIs to create a movie recommender. The final course, Python Project: pillow, tesseract, and opencv (Course 5), is an extended project in which you’ll perform optical character recognition (OCR) and object detection in images.

Career skills to jumpstart your future.

Java Programming & Software Engineering Fundamentals Specialization

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Beginner Level
No prior experience required.

Approx. 5 months to complete
Suggested 3 hours/week

Explore a Career as a Software Engineer. Learn the basics of programming and software development

Take your first step towards a career in software development with this introduction to Java—one of the most in-demand programming languages and the foundation of the Android operating system. Designed for beginners, this Specialization will teach you core programming concepts and equip you to write programs to solve complex problems. In addition, you will gain the foundational skills a software engineer needs to solve real-world problems, from designing algorithms to testing and debugging your programs.

Centered around projects, this Specialization will help you create a portfolio of work to demonstrate your new programming skills. In the capstone you will create a recommender engine similar to those used by Netflix or Amazon. Additional projects in your portfolio will include:an interactive webpage that applies filters to images, an analysis of CSV data files, an encryption program, and a predictive text generator.

Web Design for Everybody: Basics of Web Development & Coding Specialization

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Beginner Level
No prior experience required.

Approx. 29 hours to complete

Learn to Design and Create Websites. Build a responsive and accessible web portfolio using HTML5, CSS3, and JavaScript.

This Specialization covers how to write syntactically correct HTML5 and CSS3, and how to create interactive web experiences with JavaScript. Mastering this range of technologies will allow you to develop high quality web sites that, work seamlessly on mobile, tablet, and large screen browsers accessible. During the capstone you will develop a professional-quality web portfolio demonstrating your growth as a web developer and your knowledge of accessible web design. This will include your ability to design and implement a responsive site that utilizes tools to create a site that is accessible to a wide audience, including those with visual, audial, physical, and cognitive impairments.

Online learning to jumpstart your future.

IBM Data Science Professional Certificate

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Beginner Level
No prior experience required.

Approx. 10 months to complete
Suggested 4 hour/week

Kickstart your Career in Data Science & ML. Master data science, learn Python & SQL, analyze & visualize data, build machine learning models.

Data Science has been ranked as one of the hottest professions and the demand for data practitioners is booming. This Professional Certificate from IBM is intended for anyone interested in developing skills and experience to pursue a career in Data Science or Machine Learning.

This program consists of 9 courses providing you with latest job-ready skills and techniques covering a wide array of data science topics including: open source tools and libraries, methodologies, Python, databases, SQL, data visualization, data analysis, and machine learning. You will practice hands-on in the IBM Cloud using real data science tools and real-world data sets.

It is a myth that to become a data scientist you need a Ph.D. This Professional Certificate is suitable for anyone who has some computer skills and a passion for self-learning. No prior computer science or programming knowledge is necessary. We start small, re-enforce applied learning, and build up to more complex topics.

Upon successfully completing these courses you will have done several hands-on assignments and built a portfolio of data science projects to provide you with the confidence to plunge into an exciting profession in Data Science. In addition to earning a Professional Certificate from Coursera, you will also receive a digital Badge from IBM recognizing your proficiency in Data Science.

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 and are performed in the IBM Cloud (without any cost to you). Throughout this Professional Certificate you are exposed to a series of tools, libraries, cloud services, datasets, algorithms, assignments and projects that will provide you with practical skills with applicability to real jobs that employers value, including:

Tools: Jupyter / JupyterLab, Zeppelin notebooks, R Studio, and Watson Studio

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

Projects: random album generator, predict housing prices, best classifier model, battle of neighborhoods

Machine Learning

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Beginner Level
No prior experience required.

Approx. 54 hours to complete

Machine learning is the science of getting computers to act without being explicitly programmed. In the past decade, machine learning has given us self-driving cars, practical speech recognition, effective web search, and a vastly improved understanding of the human genome. Machine learning is so pervasive today that you probably use it dozens of times a day without knowing it. Many researchers also think it is the best way to make progress towards human-level AI. In this class, you will learn about the most effective machine learning techniques, and gain practice implementing them and getting them to work for yourself. More importantly, you’ll learn about not only the theoretical underpinnings of learning, but also gain the practical know-how needed to quickly and powerfully apply these techniques to new problems. Finally, you’ll learn about some of Silicon Valley’s best practices in innovation as it pertains to machine learning and AI.

This course provides a broad introduction to machine learning, datamining, and statistical pattern recognition. Topics include: (i) Supervised learning (parametric/non-parametric algorithms, support vector machines, kernels, neural networks). (ii) Unsupervised learning (clustering, dimensionality reduction, recommender systems, deep learning). (iii) Best practices in machine learning (bias/variance theory; innovation process in machine learning and AI). The course will also draw from numerous case studies and applications, so that you’ll also learn how to apply learning algorithms to building smart robots (perception, control), text understanding (web search, anti-spam), computer vision, medical informatics, audio, database mining, and other areas.

Start your future with a Business Analytics Certificate.

Applied Data Science with Python Specialization

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Beginner Level
No prior experience required.

Approx. 5 months to complete
Suggested 6 hour/week

Gain new insights into your data . Learn to apply data science methods and techniques, and acquire analysis skills.

The 5 courses in this University of Michigan specialization introduce learners to data science through the python programming language. This skills-based specialization is intended for learners who have a basic python or programming background, and want to apply statistical, machine learning, information visualization, text analysis, and social network analysis techniques through popular python toolkits such as pandas, matplotlib, scikit-learn, nltk, and networkx to gain insight into their data.

Introduction to Data Science in Python (course 1), Applied Plotting, Charting & Data Representation in Python (course 2), and Applied Machine Learning in Python (course 3) should be taken in order and prior to any other course in the specialization. After completing those, courses 4 and 5 can be taken in any order. All 5 are required to earn a certificate.

Data Science Specialization

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Beginner Level
No prior experience required.

Approx. 11 months to complete
Suggested 7 hours/week

Launch Your Career in Data Science. A ten-course introduction to data science, developed and taught by leading professors.

This Specialization covers the concepts and tools you’ll need throughout the entire data science pipeline, from asking the right kinds of questions to making inferences and publishing results. In the final Capstone Project, you’ll apply the skills learned by building a data product using real-world data. At completion, students will have a portfolio demonstrating their mastery of the material.

Start your future on Coursera today.

Business Analytics Specialization

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Beginner Level
No prior experience required.

Approx. 6 months to complete
Suggested 3 hours/week

Make Data-Driven Business Decisions. Achieve fluency in business data strategies in four discipline-specific courses.

This Specialization provides an introduction to big data analytics for all business professionals, including those with no prior analytics experience. You’ll learn how data analysts describe, predict, and inform business decisions in the specific areas of marketing, human resources, finance, and operations, and you’ll develop basic data literacy and an analytic mindset that will help you make strategic decisions based on data. In the final Capstone Project, you’ll apply your skills to interpret a real-world data set and make appropriate business strategy recommendations.

Introduction to Data Science Specialization

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Beginner Level
No prior experience required.

Approx. 4 months to complete
Suggested 3 hours/week

Launch your career in Data Science. Data Science skills to prepare for a career or further advanced learning in Data Science.

In this Specialization learners will develop foundational Data Science skills to prepare them for a career or further learning that involves more advanced topics in Data Science. The specialization entails understanding what is Data Science and the various kinds of activities that a Data Scientist performs. It will familiarize learners with various open source tools, like Jupyter notebooks, used by Data Scientists. It will teach you about methodology involved in tackling data science problems. The specialization also provides knowledge of relational database concepts and the use of SQL to query databases. Learners will complete hands-on labs and projects to apply their newly acquired skills and knowledge.

Upon receiving the certificate for completion of the specialization, you will also receive an IBM Badge as a Specialist in Data Science Foundations.

LIMITED TIME OFFER: Subscription is only $39 USD per month and gives you access to graded materials and a certificate.

Learners will complete hands-on labs and projects to apply their newly acquired skills and knowledge. You will utilize tools like Jupyter, Zeppelin, R Studio and Watson Studio. You will also work with real-world data sets and query them using SQL from Jupyter notebooks.

Online computer science courses to jumpstart your future.

Data Analysis and Presentation Skills: the PwC Approach Specialization

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Beginner Level
No prior experience required.

Approx. 6 months to complete
Suggested 3 hours/week

Make Smarter Business Decisions With Data Analysis. Understand data, apply data analytics tools and create effective business intelligence presentations.

If you are a PwC Employee, gain access to the PwC Specialization and Courses for free using the instructions on the PwC L&D Spark page or simply search “Coursera” on PwC Spark.

This Specialization will help you get practical with data analysis, turning business intelligence into real-world outcomes. We’ll explore how a combination of better understanding, filtering, and application of data can help you solve problems faster – leading to smarter and more effective decision-making. You’ll learn how to use Microsoft Excel, PowerPoint, and other common data analysis and communication tools, and perhaps most importantly, we’ll help you to present data to others in a way that gets them engaged in your story and motivated to act.

What’s more, should you enroll in these courses, you will be invited to join PwC’s talent network. Those who opt into this talent network will receive information about PwC career opportunities, thought leadership, and happenings in the PwC global network.

Please note: If you’d like to audit the courses in this Specialization, you’ll need to enroll in each course separately and then you will see the audit option.

This specialization will include a project at the end of each module and a capstone project at the end of the specialization. Each project will provide you the chance to apply the skills of that lesson. In the first module you’ll plan an analysis approach, in the second and third modules you will analyze sets of data using the Excel skills you learn. In the fourth module you will prepare a business presentation.

In the final Capstone Project, you’ll apply the skills you’ve learned by working through a mock client business problem. You’ll analyze a set of data, looking for the business insights. Then you’ll create and visualize your findings, before recording a video to present your recommendations to the client.

Learn SQL Basics for Data Science Specialization

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Beginner Level
No prior experience required.

Approx. 4 months to complete
Suggested 5 hour/week

U​se SQL commands to filter, sort, & summarize data; manipulate strings, dates, & numerical data from different sources for analysis.

This Specialization is intended for a learner with no previous coding experience seeking to develop SQL query fluency. Through four progressively more difficult SQL projects with data science applications, you will cover topics such as SQL basics, data wrangling, SQL analysis, AB testing, distributed computing using Apache Spark, and more. These topics will prepare you to apply SQL creatively to analyze and explore data; demonstrate efficiency in writing queries; create data analysis datasets; conduct feature engineering, use SQL with other data analysis and machine learning toolsets; and use SQL with unstructured data sets.

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Data Engineering with Google Cloud Professional Certificate

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Beginner Level
No prior experience required.

Approx. 4 months to complete
Suggested 4 hours/week

Advance your career in data engineering.

This program provides the skills you need to advance your career in data engineering 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 will enable data-driven decision making by collecting, transforming, and publishing data; and you’ll gain real world experience through a number of hands-on Qwiklabs projects.

You’ll also have the opportunity to practice key job skills, including designing, building, and running data processing systems; and operationalizing machine-learning models.

Upon successful completion of this program, you will earn a certificate of completion to share with your professional network and potential employers.

If you would like to become Google Cloud certified and demonstrate your proficiency to design and build data processing systems and operationalize machine learning models on Google Cloud Platform, you will need to register for, and pass the official Google Cloud certification exam.

This Professional Certificate incorporates hands-on labs using our Qwiklabs platform.

These hands on components will let you apply the skills you learn in the video lectures. Projects will incorporate topics such as Google BigQuery, which are used and configured within Qwiklabs. You can expect to gain practical hands-on experience with the concepts explained throughout the modules.

TensorFlow in Practice Specialization

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Beginner Level
No prior experience required.

Approx. 4 months to complete
Suggested 5 hours/week

Best practices for TensorFlow, a popular open-source machine learning framework to train a neural network for a computer vision applications.

Discover the tools software developers use to build scalable AI-powered algorithms in TensorFlow, a popular open-source machine learning framework.

In this four-course Specialization, you’ll explore exciting opportunities for AI applications. Begin by developing an understanding of how to build and train neural networks. Improve a network’s performance using convolutions as you train it to identify real-world images. You’ll teach machines to understand, analyze, and respond to human speech with natural language processing systems. Learn to process text, represent sentences as vectors, and input data to a neural network. You’ll even train an AI to create original poetry!

AI is already transforming industries across the world. After finishing this Specialization, you’ll be able to apply your new TensorFlow skills to a wide range of problems and projects.

In the TensorFlow in Practice Specialization, you’ll review lectures, videos, and practice assessments, that will teach you how to use TensorFlow to implement those principles so that you can start building and applying scalable models to real-world problems.