Learn the fundamentals of programming in R Work with R's conditional statements, functions, and loops Build your own functions in R Get your data in and out of R Learn the core tools for data science with R Manipulate data with the Tidyverse ecosystem of packages Systematically explore data in R The grammar of graphics and the ggplot2 package Visualise data: plot different types of data & draw insights Transform data: best practices of when and how Index, slice, and subset data Learn the fundamentals of statistics and apply them in practice Hypothesis testing in R Understand and carry out regression analysis in R Work with dummy variables Learn to make decisions that are supported by the data! Learn to make decisions that are supported by the data! R Programming is a skill you need if you want to work as a data analyst or a data scientist in your industry of choice. Data scientist is the hottest ranked profession in the US. But to do that, you need the tools and the skill set to handle data.

Artificial intelligence has become the need of the hour. From face recognition locks to registering and verifying your security for transactions, this technology is everywhere. Artificial Intelligence has positively impacted sectors like healthcare, automobile, education and more. Artificial intelligence/machine learning is a useful skill to keep under your belt, especially since it was all the rage right now. Employers are looking for someone with diverse skill sets, expressly the one who can help their companies advance into the next generation.

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Together we are going to master in depth concepts in machine learning and python programming, then apply our knowledge in building our own neural network from scratch without using any library. What you'll learn in this course will not only lay a solid foundation in your Deep Learning career, but also permit you to understand how deep learning libraries work. If you've gotten to this point, it means you are interested in mastering how neural networks work and using your skills to solve practical problems. You may already have some knowledge on Machine learning and python programming, or you may be coming in contact with these for the very first time. It doesn't matter from which end you come from, because At the end of this course, you shall be an expert with much hands-on experience.

Although learning R is not the main focus of this course, but we will implicitly learn R by diving deep into statistical concepts. The Crucial advantage of this course is not learning algorithms and machine learning but rather developing our critical thinking and understanding what the outcomes of these models represent. The course is designed to take you to step by step in a journey of R and statistics, It is packed with templates, Exercises, quizzes, and resources that will help you understand the core R language and statistical concepts that you need for Data Science and business analytics.

The course consists of 250 exercises (exercises solutions) in data science with Python. This is a great test for people who are learning the Python language and are looking for new challenges. The course is designed for people who already have basic knowledge in Python and knowledge about data science libraries. Exercises are also a good test before the interview. Many popular topics were covered in this course.

If you want to learn Java, or, if Java is your first language, or, preferred language, or, if you already know Java and have limited time to pick up other languages and want to get started quickly on building rich gui-based computer vision applications, the fun and easy way, then this course is for you. You will learn how to use Eclipse and Java to create webcam applications and image processing applications that perform innovative functions. You will also learn Java programming. After learning the basic skills taught in this course, you will be able to incorporate OpenCV into your Java Applications. This course is also ideal for Software Developers who want to learn how to add computer vision capability to their projects.

This AWS SageMaker Canvas Course will help you to become a Machine Learning Expert and will enhance your skills by offering you comprehensive knowledge, and the required hands-on experience on this newly launched Cloud based ML tool, by solving real-time industry-based projects, without needing any complex coding expertise. Most Importantly, Guidance is offered beyond the Tool – You will not only learn the Software, but important Machine Learning principles. Also, I will share the resources where to get the best possible help from, & also the sources to get public datasets to work on to get mastery in the ML domain. A Verifiable Certificate of Completion is presented to all students who undertake this AWS SageMaker Canvas course.

Data scientists, machine learning engineers, and AI researchers all have their own skillsets. But what is that one special thing they have in common? They are all masters of deep learning. We often hear about AI, or self-driving cars, or the'algorithmic magic' at Google, Facebook, and Amazon. But it is not magic - it is deep learning. And more specifically, it is usually deep neural networks – the one algorithm to rule them all.

This course is for you if you are new to Machine Learning but want to learn it without all the math. This course is also for you if you have had a machine learning course but could never figure out how to use it to solve your own problems. In this course, we will start from very scratch. This is a very applied course, so we will immediately start coding even without installation! You will see a brief bit of absolutely essential theory and then we will get into the environment setup and explain almost all concepts through code.