Learn how to use NumPy, Pandas, Seaborn, Matplotlib, Plotly, Scikit-Learn, Machine Learning, Tensorflow, and more! Are you ready to start your path to becoming a Data Scientist! This comprehensive course will be your guide to learning how to use the power of Python to analyze data, create beautiful visualizations, and use powerful machine learning algorithms! Data Scientist has been ranked the number one job on Glassdoor and the average salary of a data scientist is over $120,000 in the United States according to Indeed! Data Science is a rewarding career that allows you to solve some of the world's most interesting problems!

Learning paths are easily one of the most popular and in-demand resources we curate at the start of the new year. We've received a ton of queries recently asking when we would be releasing the learning paths for 2020. And here we are – we are thrilled to present the first learning path of 2020 for our community! The learning path for 2020 is the ultimate and most comprehensive collection of resources put together in a structured manner. This learning path is for anyone who wants to make a career in data science.

Researchers have invented a machine learning algorithm that forecasts the outcome of chemical reactions with much greater accuracy than proficient chemists and proposes ways to make complex particles, removing a weighty hurdle in drug innovation. University of Cambridge researchers have revealed that an algorithm can forecast the outcomes of complex chemical reactions with above 90% accuracy, overtaking trained chemists. The algorithm also displays chemists how to make target mixtures, providing the chemical "map" to the required destination. The outcomes are stated in two studies in the journals ACS Central Science and Chemical Communications. A central task in drug discovery and materials science is discovering ways to build complex organic molecules by chemically assembling together elementary building blocks. The problem arises when those building blocks often respond in surprising ways.

Show your working: generations of mathematics students have grown up with this mantra. Getting the right answer is not enough. To get top marks, students must demonstrate how they got there. Now, machines need to do the same. As artificial intelligence (AI) is used to make decisions affecting employment, finance or justice, as opposed to which film a consumer might want to watch next, the public will insist it explains its working.

The education board in Hiroshima Prefecture has pioneered the use of a pint-sized "surrogate robot" to realize what was previously considered impossible: allowing hospitalized students to take classes remotely without being monitored by teachers. The success of the board's tech-savvy initiative, considered an educational first in Japan, has prompted the education ministry to relax rigid requirements that have long prevented many hospitalized high school students from qualifying for class attendance. Under the board's initiative, jointly developed with Hiroshima University Hospital, a 23-centimeter-tall robot called Orihime is placed in a classroom to act as an avatar for an ill student in the hospital. The Orihime robot simultaneously records and broadcasts the content of each class for hospitalized students to watch on their tablets, enabling them to take part in classes in real time. Students not only can watch real-time footage but speak to their classmates or teachers through the robot as well. They can also command Orihime to move and make a variety of gestures, such as turning its head sideways and waving.

In the age of Alexa, YouTube recommendations, and Spotify playlists, artificial intelligence has become a way of life, improving marketing and advertising, e-commerce, and more. But what are the ethical implications of technology that collects and learns personal information? How should society navigate these issues and shape the future? A new curriculum designed for middle school students aims to help them understand just that at an early age, as they grow up surrounded by the technology. The open-source educational material, designed by an MIT team and piloted at this year's Massachusetts STEM Week this past fall, teaches students how AI systems are designed, how they can be used to influence the public -- and also how to use them to be successful in jobs of the future.

Some of the areas where data science can be used are student admissions cycle, student lifecycle management, career placements, donor relations, financial operations and research/publications. Research itself is a broad area where there are several application of AI including deep learning (natural language processing and computer vision). School admissions is a very critical area for any higher-education institute. On one hand, the institute has to make sure that the quality of students who get admitted is very high and on other hand, confirm that there should be enough good candidates to fill up the class size. The offer/acceptance ratio is important to hit a target where the institute has enough high-quality students to fill up the class size but do not have many more than the class size.

Time to set goals for expanding your programming skills while perfecting what you already know. This year, why not make a resolution to learn a new computer language? A new language under your belt--or new tools and services-- doesn't just give you more choices when deciding what projects to work on. It also helps you to better understand the strengths and weaknesses of the computer language(s) you already know as you figure out why the new language does things the way it does. Throughout this month, we will continue to help you with setting your learning goals.

Python Programming Basics and Python Object Oriented Programming Guide for Python Programmers & Python Coders in a simple and easy way with Examples, quizzes, Resources & Python Projects to master Python from zero to hero. First Python Project (CCG) to master what you will learn. Second Python Project X-O Game Classes to master what you will learn. How to use python IDLE. How to use Jupyter notebook(I python).

The Inspiration: Is it fair to say mathematicians are averse to technology? My lifelong love for math inevitably led me to an undergraduate study in mathematics. Soon after taking my first college statistics course, I realized I also had a knack for understanding and interpreting data, as well as coding in the programming language R. After graduating with a Mathematics B.Sc., I became a high school teacher. Even though I can truly say I enjoyed what I did, I still felt the need to search for a more technically challenging career path.