One of the most common problems learners have when jumping into Machine Learning and Data Science is the steep learning curve, and when you add to this the complexity of learning programming languages like Python or R you can get demotivated and lose interest fast. In this course you will learn the basic concepts of machine learning using a visual tool. Where you can just drag drop machine learning algorithms and all other functionality hiding the ugliness of code, making it much more easier to grasp the fundamental concepts. I will "hand-hold" you as we build from scratch 2 different types of supervised machine learning algorithms used in the real world, across several industries and I will explain where and how they are used. The course will teach you those fundamental concepts of machine learning by implementing practical exercises which are based on live examples.

The teaching of this course is done making the use of the "inverted classroom" model. This in simple terms means that instead of being introduced to the related material in a large lecture hall that limits itself to one-way communication, one can first watch the lecture that has been recorded by Geoffrey Hinton as a set of about 3 short videos at home before the commencement of the class, and then in class, takes place a much more dynamic discussion about it. If one is already registered for the class, you will be able to view all these videos on the Coursera website. Further details of how to do this will be given in the first lecture period.

In Data visualization with R course you will learn about Data visualization in a very systematic and easy way. R is a very powerful option in many software development domains. At its core, R is a statistical programming language that provides impressive tools for data mining and analysis, creating high-level graphics, and machine learning. R gives aspiring analysts and data scientists the ability to represent complex sets of data in an impressive way. By the end of the course, you will have enough knowledge and skill full of different visualization techniques, with the capacity to apply these abilities to real-world data sets.

Artificial intelligence (AI) is all the rage these days. Recently, the American tech major Nvidia brought together the best minds in research, academia and industry across Hyderabad, Chennai, Mumbai, Pune, Delhi and Bengaluru. The six-city developer roadshow saw over 5,000 attendees who experienced some of the best demonstrations of AI and deep learning tools, designed to meet the challenges big data presents. "The artificial intelligence revolution is here and developers who understand AI and its application in commercial applications are in demand today," said Vishal Dhupar, managing director, Nvidia – South Asia. "The first edition of Developer Connect 2017 demonstrated the passion and desire for learning within our community of highly qualified developers and it is our responsibility at Nvidia to equip our Indian tech talent to take a leading role in the AI revolution and we stay committed to this task," he added.

Get your team access to Udemy's top 2,000 courses anytime, anywhere. Cancer Genomics Neural Networks vs k-NN Classifiers: Machine Learning for Python Hackers is a crash course in Data Science and Cancer Genomics for anyone interested in cancer research. The course starts out with loading up a cancer dataset to split train and test. This course is unique in Data Science in that it uses the mglearn library for better visualization and is dedicated to providing details as such so the student can follow along with no ambiguity.

Have you always wanted to mine twitter data? Then this course is for you. This course presents example of text mining with R. Twitter text of @pycon and @udemy is used as the data to analyze. It starts by extracting text from Twitter. The extracted text is then transformed to a corpus and then a document-term matrix.

There's an increasing number of data being produced every day. This has led to the demand for skilled professionals who can analyze these data and make decisions. R is one of the popular tools which is widely used by data analysts for performing data analysis on real-world data. This Learning Path is the complete learning process to play with data. You will start with the most basic importing techniques for downloading compressed data from the Web.

About this course: Welcome to Course 3 - Models & Frameworks to Support Sales Planning – In this course, you'll go through a conceptual approach to selling models and frameworks. As a primary learning outcome of this course, we emphasize the improvement in the analytical competencies and skills to develop sales planning and management. And the learning process goes through the application of the models and frameworks that contribute to supporting these processes. This course is aimed at professionals who seek improvement in conceptual support to the sales planning process, especially with an emphasis on applying selling models and frameworks methodology. At this point of the Strategic Sales Management specialization, you have an excellent understanding of the integration of sales planning to the strategy of the company.

About this course: In this course, you will learn how to develop your Problem Solving and Creativity Skills to help you achieve success in your university studies. After completing this course, you will be able to: 1. Recognise the importance and function of problem solving and creative thought within academic study and the role of critical thought in creative ideation.

Tim Hoolihan currently works at DialogTech, a marketing analytics company focused on conversations. He is the senior director of data science there. Prior to that, he was CTO at Level Seven, a regional consulting company in the US Midwest. He is the organizer of the Cleveland R User Group.In his job, he uses deep neural networks to help automate of lot of conversation classification problems. In addition, he works on some side-projects researching other areas of artificial intelligence and machine learning.