This course prepares you for the role of Data Scientist by making you an expert in Statistics, Data Science, Big Data, R Programming, Python, and SAS. The program has been designed by Ronald Van Loon, named by Onalytica as one of the top 10 Big Data & Data Science Influencer in the world to help you master data mining, management, exploration, and carry out several industry-relevant projects.

Machine learning gives you extremely powerful insights into data, and has become so ubiquitous you see it nearly constantly while you browse the internet without even knowing it. Implementations of machine learning are as diverse as recommendation systems to self-driving cars. In this course, you'll be introduced to a unique blend of projects that will teach you what machine learning is all about and how you can use Python to create machine learning projects. Access 26 lectures & 3 hours of content 24/7 Work on six independent projects to help you master machine learning in Python Cover concepts such as classification, regression, clustering, & more Apply various machine learning algorithms Master Python's packages & libraries to facilitate computation Implement your own machine learning models

Learn how to use ElasticSearch in combination with the rest of the Elastic Stack to ship, parse, store, and analyze logs! You'll start by getting an understanding of what ElasticSearch is, what it's used for, and why it's important before being introduced to the new features of Elastic Search 5.0. Access 35 lectures & 3 hours of content 24/7 Go through each of the fundamental concepts of ElasticSearch such as queries, indices, & aggregation Add more power to your searches using filters, ranges, & more See how ElasticSearch can be used w/ other components like LogStash, Kibana, & Beats Build, test, & run your first LogStash pipeline to analyze Apache web logs

A/B testing is used everywhere, from marketing, retail, news feeds, online advertising, and much more. If you're a data scientist, and you want to tell the rest of the company, "logo A is better than logo B," you're going to need numbers and stats to prove it. That's where A/B testing comes in. In this course, you'll do traditional A/B testing in order to appreciate its complexity as you elevate towards the Bayesian machine learning way of doing things. Access 40 lectures & 3.5 hours of content 24/7 Improve on traditional A/B testing w/ adaptive methods Learn about epsilon-greedy algorithm & improve upon it w/ a similar algorithm called UCB1 Understand how to use a fully Bayesian approach to A/B testing

When people talk about artificial intelligence, they usually don't mean supervised and unsupervised machine learning. These tasks are pretty trivial compared to what we think of AIs doing—playing chess and Go, driving cars, etc. Reinforcement learning has recently become popular for doing all of that and more. Reinforcement learning opens up a whole new world. It's lead to new and amazing insights both in behavioral psychology and neuroscience. It's the closest thing we have so far to a true general artificial intelligence, and this course will be your introduction. Access 71 lectures & 5.5 hours of content 24/7 Discuss the multi-armed bandit problem & the explore-exploit dilemma Learn ways to calculate means & moving averages and their relationship to stochastic gradient descent Explore Markov Decision Processes, Dynamic Programming, Monte Carlo, & Temporal Difference Learning Understand approximation methods

This course is all about the application of deep learning and neural networks to reinforcement learning. The combination of deep learning with reinforcement learning has led to AlphaGo beating a world champion in the strategy game Go, it has led to self-driving cars, and it has led to machines that can play video games at a superhuman level. Unlike supervised and unsupervised learning algorithms, reinforcement learning agents have an impetus—they want to reach a goal. In this course, you'll work with more complex environments, specifically, those provided by the OpenAI Gym. Access 52 lectures & 5 hours of content 24/7 Extend your knowledge of temporal difference learning by looking at the TD Lambda algorithm Explore a special type of neural network called the RBF network Look at the policy gradient method Examine Deep Q-Learning

Variational autoencoders and GANs have been two of the most interesting recent developments in deep learning and machine learning. GAN stands for generative adversarial network, where two neural networks compete with each other. Unsupervised learning means you're not trying to map input data to targets, you're just trying to learn the structure of that input data. In this course, you'll learn the structure of data in order to produce more stuff that resembles the original data. Access 41 lectures & 5.5 hours of content 24/7 Incorporate ideas from Bayesian Machine Learning, Reinforcement Learning, & Game Theory Discuss variational autoencoder architecture Discover GAN basics

“Data Scientist: The Sexiest Job of the 21st Century”– Harvard Business Review Looking to break into the field of Data Science, or simply gain a solid understanding of the discipline? Want to better understand the importance of data, and how to use it? A Data Scientist’s skillset is the most sought after skill across a wide range of industries. The median Data Scientist salary is $91k per annum according to Payscale, and Glassdoor awarded it Best Job in America (2016 & 2017), with a job satisfaction score of 4.4 / 5. By studying this data science course online, you will quickly master the basics of the discipline, opening you up to a wealth of new job opportunities and propelling you into a fulfilling and lucrative career. Or if you are not up for taking the leap into data science, but would like a better understanding, or you work with data scientists and would like to talk intelligently about their work and collaborate better, this online course is also ideal for you. Get ready to impress your data scientist colleagues and gain their respect with your insight and knowledge after completing this course! What you get with this course: 39 modules of training (full syllabus below) A blended learning experience where you’ll learn from a mix of videos, text and interactive quizzes You’ll have an excellent data science foundation to take the next step for your career In this course you will learn: Learn how to use your analytical skills to manipulate large data sets Develop business acumen, so findings are applicable in the real world Master statistics, to separate vital signals from irrelevant noise Grasp the basics R programming language and advanced Excel techniques Understand the core elements of data science, allowing you to solve real business problems Read HBR’s Article about Data Science here. More about us: We have nearly 1 million students in total and have been teaching courses online since 2009 Our training is personal. If you are familiar with certain elements of Data Science you can use the filter to show you which parts of the course to skip. Our platform is award winning and improving all the time. If you are not 100% happy with your EwB Data Science course, you have 30 days to exchange or refund Sample content:

Intellipaat Data Science certification training lets you master data analysis, deploying R Statistical computing, machine learning algorithms, K-Means Clustering, NaïveBayes, connecting R with Hadoop framework, work on real world projects and case studies. You will learn time series analysis, business analytics and more in this popular course.

Learn Hadoop and get certified & bag one of the highest paying IT jobs in current times.