Gartner’s top strategic predictions for 2018 and how Coursera specializations would help boost your career

Gartner’s top strategic predictions for 2018 and beyond are here.In this post,I have tried to map the trend with course specializations offered by Coursera. I’m sure this will help boost your career and expand your knowledge. Check them out, and start enrolling today!

Gartner calls the entwining of people, devices, content and services the intelligent digital mesh. It’s enabled by digital models, business platforms and a rich, intelligent set of services to support digital business.

Intelligent: How AI is seeping into virtually every technology and with a defined, well-scoped focus can allow more dynamic, flexible and potentially autonomous systems.

Trend #1 : AI Foundations

The ability to use AI to enhance decision making, reinvent business models and ecosystems, and remake the customer experience will drive the payoff for digital initiatives through 2025.

• Machine Learning – Stanford University 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.
• Neural Networks and Deep Learning – deeplearning.ai In this course, you will learn the foundations of deep learning. When you finish this class, you will: (i)Understand the major technology trends driving Deep Learning (ii) Be able to build, train and apply fully connected deep neural networks (iii)  Know how to implement efficient (vectorized) neural networks (iv) Understand the key parameters in a neural network’s architecture This course also teaches you how Deep Learning actually works, rather than presenting only a cursory or surface-level description. So after completing it, you will be able to apply deep learning to a your own applications. If you are looking for a job in AI, after this course you will also be able to answer basic interview questions.

Trend #2 : Intelligent Apps and Analytics

Over the next few years every app, application and service will incorporate AI at some level. AI will run unobtrusively in the background of many familiar application categories while giving rise to entirely new ones.

• Machine Learning with Big Data This course provides an overview of machine learning techniques to explore, analyze, and leverage data. You will be introduced to tools and algorithms you can use to create machine learning models that learn from data, and to scale those models up to big data problems.
• Big Data Specialization You will gain an understanding of what insights big data can provide through hands-on experience with the tools and systems used by big data scientists and engineers. Previous programming experience is not required! You will be guided through the basics of using Hadoop with MapReduce, Spark, Pig and Hive. By following along with provided code, you will experience how one can perform predictive modeling and leverage graph analytics to model problems. This specialization will prepare you to ask the right questions about data, communicate effectively with data scientists, and do basic exploration of large, complex datasets. In the final Capstone Project, developed in partnership with data software company Splunk, you’ll apply the skills you learned to do basic analyses of big data.
• Advanced Machine Learning This specialization gives an introduction to deep learning, reinforcement learning, natural language understanding, computer vision and Bayesian methods. Top Kaggle machine learning practitioners and CERN scientists will share their experience of solving real-world problems and help you to fill the gaps between theory and practice. Upon completion of 7 courses you will be able to apply modern machine learning methods in enterprise and understand the caveats of real-world data and settings.

Trend #3 : Intelligent Things

Intelligent things use AI and machine learning to interact in a more intelligent way with people and surroundings. Some intelligent things wouldn’t exist without AI, but others are existing things (i.e., a camera) that AI makes intelligent (i.e., a smart camera.)

• Machine Learning – Stanford University 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.
• 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.AI is transforming multiple industries. After finishing this specialization, you will likely find creative ways to apply it to your work.
• Neural Networks and Deep Learning – deeplearning.a In this course, you will learn the foundations of deep learning. When you finish this class, you will: (i)Understand the major technology trends driving Deep Learning (ii) Be able to build, train and apply fully connected deep neural networks (iii)  Know how to implement efficient (vectorized) neural networks (iv) Understand the key parameters in a neural network’s architecture This course also teaches you how Deep Learning actually works, rather than presenting only a cursory or surface-level description. So after completing it, you will be able to apply deep learning to a your own applications. If you are looking for a job in AI, after this course you will also be able to answer basic interview questions.

Trend No. 4: Digital Twins

A digital twin is a digital representation of a real-world entity or system. In the context of IoT, digital twins are linked to real-world objects and offer information on the state of the counterparts, respond to changes, improve operations and add value.

• IoT Specialization This Specialization covers the development of Internet of Things (IoT) products and services—including devices for sensing, actuation, processing, and communication—to help you develop skills and experiences you can employ in designing novel systems. The Specialization has theory and lab sections. In the lab sections you will learn hands-on IoT concepts such as sensing, actuation and communication. In the final Capstone Project, developed in partnership with Qualcomm, you’ll apply the skills you learned on a project of your choice using the DragonBoard 410c platform.
• Emerging Technologies: From Smartphones to IoT to Big Data This Specialization covers the concepts of the most important information technologies that you have been using and will be using throughout your entire life! Topics covered include Smartphones, OS, Cloud Computing, Big Data, CDN, Wi-Fi, Bluetooth, Mobile Communication, LTE, LTE-Advanced, IoT, AR, IPv4, IPv6, TCP, UDP, and Internet operations. The Specialization concludes with a Capstone project that allows you to apply the skills you’ve learned throughout the courses.

Trend No. 5: Cloud to the Edge

Edge computing describes a computing topology in which information processing and content collection and delivery are placed closer to the sources of this information.

• Architecting Smart IoT Devices This course will teach you how to develop an embedded systems device. In order to reduce the time to market, many pre-made hardware and software components are available today. You’ll discover all the available hardware and software components, such as processor families, operating systems, boards and networks. You’ll also learn how to actually use and integrate these components. At the end of the course you will be ready to start architecting and implementing your own embedded device! You’ll learn how to debug and finetune your device and how to make it run on a low power supply.
• A developer’s guide to the Internet of Things (IoT) This course is an entry level introduction to developing and deploying solutions for the Internet of Things. It will focus on capturing data from a trusted device and sending the data to a cloud platform where it can be exploited by the many services available. You will explore all the steps required to create a basic IoT solution using a popular device, the Raspberry Pi, and a trial version of the cloud-based IBM Watson IoT Platform. You will learn: Quickly create applications that leverage connectivity and analytics as part of an integrated IoT platform. Use Node-RED, an open-source visual application development environment, on both the device and the cloud. Create a basic IoT solution by leveraging pre-built blocks of code that abstracts and speeds the development process. Use APIs to access the platform and explore the different connectivity options for various devices, gateways and applications. Explore options to ensure your solution makes best use of the captured data.

Trend No. 6: Conversational Platforms

Conversational platforms will drive a paradigm shift in which the burden of translating intent shifts from user to computer.

• Natural Language Processing This course covers a wide range of tasks in Natural Language Processing from basic to advanced: sentiment analysis, summarization, dialogue state tracking, to name a few. Upon completing, you will be able to recognize NLP tasks in your day-to-day work, propose approaches, and judge what techniques are likely to work well. The final project is devoted to one of the most hot topics in today’s NLP. You will build your own conversational chat-bot that will assist with search on StackOverflow website. The project will be based on practical assignments of the course, that will give you hands-on experience with such tasks as text classification, named entities recognition, and duplicates detection.

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Trend No. 7: Immersive Experience

Augmented reality (AR), virtual reality (VR) and mixed reality are changing the way that people perceive and interact with the digital world.

• Virtual reality Specialization This specialisation from the University of London will introduce you to virtual reality.Virtual reality is one of the most highly requested skill sets in the jobs market, and this specialisation will give you an introduction to the subject and key skills in the field. You will hear from world-leading lecturers and industry experts, use Unity to develop your own VR environment, and end the specialisation by creating your first VR game.
• Getting started with Augmented Reality This course will teach you the basics of developing mobile applications using Mixed and Augmented Reality (MAR) technologies.Through hands-on projects, you’ll learn practical techniques to rapidly and easily prototype three different applications for Android smartphones and tablets – even with no previous coding experience.
• Building Interactive 3D Characters and Social VR Meeting another person is one of the most amazing experiences you can have in Virtual Reality. It is quite unlike communicating through any other medium except a real life face-to-face conversation. Because the other person is life size and shares a virtual space with you, body language works in a way that cannot be done on a flat screen. This course will enable you to create realistic social interactions in VR. You will learn about both the psychology of social interaction and the practical skills to implement it in Unity3D. We will take you through the basics of 3D character animation and how to create body language. You will learn about how to make characters that can respond to players’ speech and body language. You will also learn about avatars: the virtual representation of other players, and agents: computer controlled NPC characters and how to implement both of them.

Trend No. 8: Blockchain

Blockchain is a shared, distributed, decentralized and tokenized ledger that removes business friction by being independent of individual applications or participants.

• Bitcoin and Cryptocurrency Technologies – IBM If you’re a software developer and new to blockchain, this is the course for you. Several experienced IBM blockchain developer advocates will lead you through a series of videos that describe high-level concepts, components, and strategies on building blockchain business networks. You’ll also get hands-on experience modeling and building blockchain networks as well as create your first blockchain application. The first part of this course covers basic concepts of blockchain, and no programming skills are required. However, to complete three of the four labs, you must understand basic software object-oriented programming and how to use the command line. It’s also helpful, but not required, that you can write code in JavaScript. When you complete the course, you should understand what a blockchain business network is, how to build and model a simple blockchain solution, and the role of the developer in creating blockchain applications.

Trend No. 9: Event-Driven

Digital businesses rely on the ability to sense and be ready to exploit new digital business moments. Business events reflect the discovery of notable states or state changes, such as completion of a purchase order.

Trend No. 10: Continuous Adaptive Risk and Trust

Digital business creates a complex, evolving security environment. The use of increasingly sophisticated tools increases the threat potential. Continuous adaptive risk and trust assessment (CARTA) allows for real-time, risk and trust-based decision making with adaptive responses to security-enable digital business.

• Cyber security and the Internet of Things

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