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Trending Data Science Skills : Data Science Introductory Courses And Specializations

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Demand for data-driven decision makers continues to grow.  There’s a projected 15% growth in data science careers and 110,000 new jobs for data-driven decision makers by 2020. According to Coursera’s analysis of global skills, the most sought-after data science skills include math, statistics, machine learning, data management, statistical programming, and data visualization.

Whether you’re looking advance your Python learning or just beginning to dip your toes into the world of data science, Coursera got you covered. Take the next step with one of these new courses and Specializations from world-class universities and companies:

Just getting started? Way to go! Here are some great introductory courses and Specializations:

1. AI for Everyone by

Having an understanding of the capabilities of AI and machine learning is important for any role in data science. In this introductory course, you’ll learn AI terminology, what AI can (and cannot) do, how to spot opportunities to apply AI to problems in your own organization, what it feels like to build machine learning and data science projects, how to work with an AI team and build an AI strategy in your company, and more.

2. Code Free Data Science by UCSD

In this introductory course, you’ll acquire new skills to apply predictive algorithms to real data, evaluate, validate and interpret the results without any prerequisites for any kind of programming. You’ll gain the essential skills to design, build, verify and test predictive models.

3. GIS, Mapping, and Spatial Analysis Specialization by University of Toronto

Launch your career in mapping and geographic information systems. Learn the concepts, tools, and techniques to make great maps that answer geographic questions. You will learn practical skills that can be applied to your own work using cutting-edge software created by Esri Inc., the world’s leading GIS company.

4. Foundations of Data Science: K-Means Clustering in Python by University of London

This beginner level course, designed by an academic team from Goldsmiths, University of London, will quickly introduce you to the core concepts of Data Science to prepare you for more intermediate and advanced Data Science courses. It focuses on the basic mathematics, statistics, and programming skills that are necessary for typical data analysis tasks.

Ready to take your learning to the next level? Check out these intermediate courses and Specializations:

1. Tensorflow in Practice Specialization by

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!

2. Clinical Data Science Specialization by University of Colorado

In this Specialization you will learn how to: understand electronic health record data types and structures, deploy basic informatics methodologies on clinical data,  provide appropriate clinical and scientific interpretation of applied analyses, and anticipate barriers in implementing informatics tools into complex clinical settings. You will demonstrate your mastery of these skills by completing practical application projects using real clinical data.

3. Python Data Products for Predictive Analytics Specialization by University of California, San Diego

This Specialization is for anyone who is proficient with the basics of Python. You’ll start by creating your first data strategy. You’ll also develop statistical models, devise data-driven workflows, and learn to make meaningful predictions for a wide-range of business and research purposes. Finally, you’ll use design thinking methodology and data science techniques to extract insights from a wide range of data sources. This is your chance to master one of the technology industry’s most in-demand skills.

4. Machine Learning Using SAS Viya by SAS

This course covers the theoretical foundation for different techniques associated with supervised machine learning models. You’ll use Model Studio, the pipeline flow interface in SAS Viya that enables you to prepare, develop, compare, and deploy advanced analytics models. You’ll learn to train supervised machine learning models to make better decisions on big data. The SAS applications used in this course make machine learning possible without programming or coding.

5. Statistics with SAS by SAS

This introductory course is for SAS software users who perform statistical analyses using SAS/STAT software. The course focuses on t-tests, ANOVA, and linear regression, and also includes a brief introduction to logistic regression.

6. Applied AI: Artificial Intelligence with IBM Watson Specialization by IBM

This Specialization will give you a firm understanding of AI, its applications, and its use cases. You will become familiar with IBM Watson AI services and APIs. If you have no programming background, you will be able to create AI driven chatbots as well as pick up practical Python skills to work with AI. The courses will also enable you to apply pre-built AI smarts to your products and solutions.

Can’t get enough of data science? Explore the wide variety of skills and career options at our Data Science Academy.

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