New Year Resolution 2020 #2: Learn something new everyday
According to Gartner Top 10 Strategic Technology Trends for 2020, Hyperautomation,Multiexperience, Human Augmentation, Blockchain, and Empowered Edge will drive disruption and new business models.
Here’s the best compilation that will boost your career and expand your knowledge. Check them out and start learning today!
- Most Popular courses of 2019
- #1.Machine Learning (2.45 Million Enrollments)
- #2.Learning How to Learn: Powerful mental tools to help you master tough subjects (1.75 Million Enrollments)
- #3.Programming for Everybody (860K Enrollments)
- #4.Successful Negotiation: Essential Strategies and Skills (552K Enrollments)
- #5.Chinese for Beginners (549K Enrollments)
- #6.Neural Networks and Deep Learning (423K Enrollments)
- #7.R Programming (414K Enrollments)
- #8.The Science of Well-Being (384K Enrollments)
- #9.Grammar and Punctuation (357K Enrollments)
- #10.English for Career Development (338K Enrollments)
- Trending Courses
- #1.Coursera Specializations
- #2.Artificial Intelligence
- #3.Machine Learning
- #4.Data Science
- #5.Deep Learning
- #6.Course Collections
- #7.Business Specializations
- #8.Online nano degree programs
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Most Popular courses of 2019
#1.Machine Learning (2.45 Million Enrollments)
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.
#2.Learning How to Learn: Powerful mental tools to help you master tough subjects (1.75 Million Enrollments)
This course gives you easy access to the invaluable learning techniques used by experts in art, music, literature, math, science, sports, and many other disciplines. We’ll learn about the how the brain uses two very different learning modes and how it encapsulates (“chunks”) information. We’ll also cover illusions of learning, memory techniques, dealing with procrastination, and best practices shown by research to be most effective in helping you master tough subjects.
Using these approaches, no matter what your skill levels in topics you would like to master, you can change your thinking and change your life. If you’re already an expert, this peep under the mental hood will give you ideas for: turbocharging successful learning, including counter-intuitive test-taking tips and insights that will help you make the best use of your time on homework and problem sets. If you’re struggling, you’ll see a structured treasure trove of practical techniques that walk you through what you need to do to get on track. If you’ve ever wanted to become better at anything, this course will help serve as your guide.
This course can be taken independent of, concurrent with, or prior to, its companion course, Mindshift. (Learning How to Learn is more learning focused, and Mindshift is more career focused.)
This course aims to teach everyone the basics of programming computers using Python. We cover the basics of how one constructs a program from a series of simple instructions in Python. The course has no pre-requisites and avoids all but the simplest mathematics. Anyone with moderate computer experience should be able to master the materials in this course.
In the course, you’ll learn about and practice the four steps to a successful negotiation: (1) Prepare: Plan Your Negotiation Strategy (2) Negotiate: Use Key Tactics for Success (3) Close: Create a Contract (4) Perform and Evaluate: The End Game
To successfully complete this course and improve your ability to negotiate, you’ll need to do the following:
(1) Watch the short videos (ranging from 5 to 20 minutes). The videos are interactive and they include questions to test your understanding of negotiation strategy and skills. You can speed up or slow down videos to match your preferred pace for listening. Depending on your schedule, you can watch the videos over a few weeks or you can binge watch them. A learner who binge-watched the course concluded that “It’s as good as Breaking Bad.” Another learner compared the course to “House of Cards.” Both shows contain interesting examples of complex negotiations!
(2) Test your negotiation skills by completing the negotiation in Module 6. You can negotiate with a local friend or use Discussions to find a partner from another part of the world. Your negotiation partner will give you feedback on your negotiation skills. To assist you with your negotiations, I have developed several free negotiating planning tools that are related to the course. These tools and a free app are available at http://negotiationplanner.com/
(3) Take the final exam. To successfully complete the course, you must answer 80% of the questions correctly. The exam is a Mastery Exam, which means that you can take it as many times as you want until you master the material.
This course is also available in Spanish and Portuguese. To join the fully translated Spanish version, visit this page: https://www.coursera.org/learn/negociacion/
Nowadays, there is an increasing number of people who are interested in Chinese culture and language. And it is useful to know about the language when coming to China for travel or business. This is an ABC Chinese course for beginners, including introduction of phonetics and daily expressions. After taking this class, learners can have a basic understanding of Chinese Mandarin and make basic conversations of daily living such as exchanging personal information, talking about daily arrangements and food, asking about price, introducing the city and the weather, telling your hobbies etc. Selected topics and situations come from real life scenarios and can be used for everyday communications. In addition to the dialogues, the selection of reading materials and practice activities will make the content as rich and varied as possible, in order to stimulate the learners’ interests. This is an elementary course on Chinese speaking. The learners don’t need to study Chinese characters, so it is easier to follow and complete this course.
If you want to break into cutting-edge AI, this course will help you do so. Deep learning engineers are highly sought after, and mastering deep learning will give you numerous new career opportunities. Deep learning is also a new “superpower” that will let you build AI systems that just weren’t possible a few years ago.
In this course, you will learn the foundations of deep learning. When you finish this class, you will:
– Understand the major technology trends driving Deep Learning
– Be able to build, train and apply fully connected deep neural networks
– Know how to implement efficient (vectorized) neural networks
– 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.
In this course you will learn how to program in R and how to use R for effective data analysis. You will learn how to install and configure software necessary for a statistical programming environment and describe generic programming language concepts as they are implemented in a high-level statistical language. The course covers practical issues in statistical computing which includes programming in R, reading data into R, accessing R packages, writing R functions, debugging, profiling R code, and organizing and commenting R code. Topics in statistical data analysis will provide working examples.
In this course you will engage in a series of challenges designed to increase your own happiness and build more productive habits. As preparation for these tasks, Professor Laurie Santos reveals misconceptions about happiness, annoying features of the mind that lead us to think the way we do, and the research that can help us change. You will ultimately be prepared to successfully incorporate a specific wellness activity into your life.
The first course in this specialization is a refresher on some tools needed for good writing. It will help prepare you for the other courses. You will need about 10 hours to complete this first course. Writing is a skill and to learn a skill well, you need to practice. In this course, you will watch short video lectures and then practice and discuss what you have learned. Make sure you take good notes and use the peer discussions to ask questions. Then you’ll be able to remember the rules you learn in this course when you start writing essays in the next course.
After completing this course, you will be able to:
– identify the correct verb tenses to use
– use commas effectively – utilize several different sentence types
– write more effectively in English
#10.English for Career Development (338K Enrollments)
This course is designed for non-native English speakers who are interested in advancing their careers in the global marketplace. In this course, you will learn about the job search, application, and interview process in the United States, while comparing and contrasting the same process in your home country. This course will also give you the opportunity to explore your global career path, while building your vocabulary and improving your language skills to achieve your professional goals. The first unit in this course will introduce the U.S. job application process and provide strategies for identifying the jobs that match your interests and skills. Unit 2 will take you through the steps necessary to produce a professional-looking resume. In unit 3, you will work to develop a clear and concise cover letter. The final unit of the course focuses on networking and interview skills.
Coursera Specialization is a series of courses that help you master a skill. To begin, you can 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.
Every Specialization includes a hands-on project. You’ll need to successfully finish the project(s) to complete the Specialization and earn your certificate. If the Specialization includes a separate course for the hands-on project, you’ll need to finish each of the other courses before you can start it.
When you finish every course and complete the hands-on project, you’ll earn a Certificate that you can share with prospective employers and your professional network.
Checkout ULTIMATE GUIDE to Coursera Specializations( more than 100+ specializations covered).
There is huge enterprise-level interest in artificial intelligence projects and their potential to fundamentally change the dynamics of business value. However,biggest pain point that emerged from Gartner’s CIO survey was the lack of specialized skills in AI, with 47% of CIOs reporting that they needed new skills for AI projects.With Gartner predicting AI as #2 in Top 10 Strategic Technology Trends for 2019.There is need for AI engineers to build, implement, and maintain AI projects.Here’s best compilation of Udemy Artificial Intelligence Courses.
- TOP 15 Udemy Artificial Intelligence Courses
- Applied AI: Artificial Intelligence with IBM Watson Specialization
- AI For Everyone from Andrew Ng (Level: Beginner)
- AI Foundations for Everyone Specialization from IBM
Machine learning algorithms build a mathematical model of sample data, known as “training data”, in order to make predictions or decisions without being explicitly programmed to perform the task. The types of machine learning algorithms differ in their approach, the type of data they input and output, and the type of task or problem that they are intended to solve. Supervised learning algorithms build a mathematical model of a set of data that contains both the inputs and the desired outputs. Unsupervised learning algorithms take a set of data that contains only inputs, and find structure in the data, like grouping or clustering of data points. The algorithms, therefore, learn from test data that has not been labeled, classified or categorized.
Ninety percent of all the world’s data has been created in the last two years. Business around the world generate approximately 450 billion transactions a day. The amount of data collected by all organizations is approximately 2.5 exabytes a day. That number doubles every month. That means, there is always an exponential need for Machine learning engineers to build, implement, and maintain machine learning systems, algorithms in technology products with a focus on machine learning system reliability, performance, and scalability.
- TOP 25 Udemy Machine Learning courses
- TOP 25 Udemy Machine Learning courses (Level – Intermediate)
- 17 Algorithms Machine Learning Engineers Need to Know
- TOP 22 Most Popular Deep Learning Courses on Udemy
Data Science has been ranked as one of the hottest professions and the demand for data practitioners is booming. Data Scientists perform sophisticated empirical analysis to understand and make predictions about complex systems. They draw on methods and tools from probability and statistics, mathematics, and computer science and primarily focus on extracting insights from data. They communicate results through statistical models, visualizations, and data products.
Per the IBM study, By 2020 the number of Data Science and Analytics job listings is projected to grow by nearly 364,000 listings to approximately 2,720,000. The following summary graphic from the study highlights how in-demand data science and analytics skill sets are today and are projected to be through 2020.
- ULTIMATE Guide to Data Science Courses (Over 65+ courses covered)
- TOP 35 Most Popular Data Science courses on Udemy
Unlike traditional machine learning, Deep learning attempts to simulate how our brains learn and process information by creating artificial “neural networks” capable of extracting complicated thoughts and relationships with data. Deep learning models enhance in order to generate more precise ideas and predictions through complicated pattern recognition in images, text, sounds, and other information.
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 CNNs, RNNs, LSTM, Adam, Dropout, BatchNorm, Xavier/He initialization, and more. You will be working on industry case studies from various domains like 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.
- #1.Deep Learning
- #2.Convolutional Neural Networks
- #3.Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization
- #4.Neural Networks and Deep Learning
- #5.Sequence Models
- #6.Structuring Machine Learning Projects
- #7.AI For Everyone
- #8.Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning
- #9.Convolutional Neural Networks in TensorFlow
- #10.TensorFlow in Practice
- #11.Natural Language Processing in TensorFlow
- #12.Sequences, Time Series and Prediction
- IBM Courses Collection
- Google Cloud Courses Collection
- Johns Hopkins University Courses Collection
- Trending Skill : Deep Learning Course Collection
- Trending Skill : Python Curated Course Collection
TOP 9 Business specialization to build a foundation of core business skills in marketing, finance, accounting, and operations.
- #1.Strategising: Management for Global Competitive Advantage Specialization
- #2.Leading: Human Resource Management and Leadership Specialization
- #3.Digital Marketing Specialization
- #4.Strategic Leadership and Management Specialization
- #5.Managerial Economics and Business Analysis Specialization
- #6.Value Chain Management Specialization
- #7.Financial Management Specialization
- #8.Global Challenges in Business Specialization
- #9.Innovation: From Creativity to Entrepreneurship Specialization
#8.Online nano degree programs
Online Degree learning experience gives you the ability to study on your own schedule and earn credit as you complete your course assignments. For a breakthrough price, you’ll learn from top university instructors and graduate with an industry-relevant university credential.
- Data Analyst
- Data Engineer
- Programming for Data Science
- Robotics Software Engineer
- Data Structures and Algorithms
- Introduction to Programming
- Predictive Analytics for Business
- Programming for Data Science
- Digital Marketing
- AI Programming with Python
- Business Analytics
- Full Stack Web Developer
- Intro to Self-Driving Cars Nanodegree
- Deep Learning
- Artificial Intelligence
- Machine Learning Engineer
- Android Developer
- Android Basics
- Computer Vision
- Become a Digital Freelancer
- Self Driving Car Engineer Nanodegree
- Flying Car and Autonomous Flight Engineer Nanodegree
- Data Scientist
- Deep Reinforcement Learning
- Blockchain Developer
- Introduction to Machine Learning Nanodegree Program
- iOS Developer
- C++ Nanodegree Program
- Marketing Analytics
- Front End Web Developer
- Natural Language Processing
- Artificial Intelligence for Trading
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