Year in Review – 10 Most Popular Coursera Specializations 2018

Coursera Specialization is a series of courses that helps you master a skill. To begin, enroll in the Specialization directly, or review its courses and choose the one you’d like to start with. When you subscribe to a course that is part of a Specialization, you’re automatically subscribed to the full Specialization. You can either complete just one course or you can pause your learning or end your subscription at any time.

In this post,we take look at most popular specializations of 2018 that will help boost your career and expand your knowledge. Check them out, and start enrolling today!

#1.Python for Everybody Specialization

Level – Beginner

This Specialization 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.

#2.An Introduction to Programming the Internet of Things (IOT) Specialization

Level – Beginner

This Specialization covers embedded systems, the Raspberry Pi Platform, and the Arduino environment for building devices that can control the physical world. In the final Capstone Project, you’ll apply the skills you learned by designing, building, and testing a microcontroller-based embedded system, producing a unique final project suitable for showcasing to future employers. Please note that this specialization does not offer discussion forums.

#3.Deep Learning Specialization

Level – Intermediate

Deep Learning is one of the most highly sought after skills in tech. We will help you become good at Deep Learning.

In five courses, you will learn the foundations of Deep Learning, understand how to build neural networks, and learn how to lead successful machine learning projects. You will learn about Convolutional networks, RNNs, LSTM, Adam, Dropout, BatchNorm, Xavier/He initialization, and more. You will work on case studies from healthcare, autonomous driving, sign language reading, music generation, and natural language processing. You will master not only the theory, but also see how it is applied in industry. You will practice all these ideas in Python and in TensorFlow, which we will teach.

You will also hear from many top leaders in Deep Learning, who will share with you their personal stories and give you career advice.

AI is transforming multiple industries. After finishing this specialization, you will likely find creative ways to apply it to your work.

#4.Architecting with Google Cloud Platform Specialization

Level – Intermediate

This specialization introduces participants to the comprehensive and flexible infrastructure and platform services provided by Google Cloud Platform. Through a combination of presentations, demos, and hands-on labs, participants explore and deploy solution elements, including infrastructure components such as networks, systems and applications services. This course also covers deploying practical solutions including securely interconnecting networks, customer-supplied encryption keys, security and access management, quotas and billing, and resource monitoring.

This class is intended for the following participants:

• Cloud Solutions Architects, DevOps Engineers.
• Individuals using Google Cloud Platform to create new solutions or to integrate existing systems, application environments, and infrastructure with the Google Cloud Platform.

This Specialization has updated, improved content that can help you if you are preparing for the Google Certified Professional – Cloud Architect exam as well as the Associate Cloud Engineer exam.

#5.Data Science Specialization

Level – Beginner

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.

#6.Google IT Support Professional Certificate

Level – Beginner

Google

This five-course certificate, developed by Google, includes innovative curriculum designed to prepare you for an entry-level role in IT support. A job in IT can mean in-person or remote help desk work in a small business or at a global company like Google. If you’ve been tinkering with IT or are new to the field, you’re at the right place. The program is part of Grow with Google, a Google initiative to help create economic opportunities for all Americans. Check out this video to learn more.

Upon completion of the certificate, you can share your information with top employers like Cognizant, GE Digital, H&R Block, Hulu, J.M. Smucker, Infosys, Intel, KForce, MCPc, PNC Bank, RICOH USA, Sprint, TEKSystems, UPMC, Veterans United Home Loans, Walmart and their subsidiaries, and of course, Google.

Through a mix of video lectures, quizzes, and hand-on labs and widgets, the program will introduce you to troubleshooting and customer service, networking, operating systems, system administration and security. Along the way, you’ll hear from Googlers with unique backgrounds whose own foundation in IT support served as a jumping off point for their careers.

By dedicating 8-10 hours a week, you can complete the certificate in about eight months. You can skip through content that you might already know and speed ahead to the graded assessments.

#7.Machine Learning Specialization

Level – Intermediate

This Specialization from leading researchers at the University of Washington introduces you to the exciting, high-demand field of Machine Learning. Through a series of practical case studies, you will gain applied experience in major areas of Machine Learning including Prediction, Classification, Clustering, and Information Retrieval. You will learn to analyze large and complex datasets, create systems that adapt and improve over time, and build intelligent applications that can make predictions from data.

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#8.Applied Data Science with Python Specialization

Level – Intermediate

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.

#9.Career Success Specialization

Level – Beginner

This series of courses will help you build, develop and hone the essential skills needed to improve your employability and advancement in today’s dynamic workforce. The courses in this Specialization may be taken in any order. Each course can also be taken independently. The Specialization concludes with a Capstone project that will give you the opportunity to integrate and apply the skills you have gained throughout the courses to your individual and organizational needs.

#10.Developing Applications with Google Cloud Platform Specialization

Level – Intermediate

In this specialization, application developers learn how to design, develop, and deploy applications that seamlessly integrate components from the Google Cloud ecosystem. Through 4 courses and a combination of presentations, demos, and hands-on labs, participants learn how to use GCP services and pre-trained machine learning APIs to build secure, scalable, and intelligent cloud-native applications.

This class is intended for application developers who want to build cloud-native applications or redesign existing applications that will run on Google Cloud Platform.

Specialization objectives

This course teaches participants the following skills:

• Use best practices for application development.
• Choose the appropriate data storage option for application data.
• Implement federated identity management.
• Develop loosely coupled application components or microservices.
• Integrate application components and data sources.
• Debug, trace, and monitor applications.
• Perform repeatable deployments with containers and deployment services.
• Choose the appropriate application runtime environment; use Google Container Engine as a runtime environment and later switch to a no-ops solution with Google App Engine flexible environment.

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