Artificial Intelligence is becoming progressively more relevant in today's world. The rise of AI has the potential to transform our future more than any other technology. By using the power of algorithms, you can develop applications which intelligently interact with the world around you, from building intelligent recommender systems to creating self-driving cars, robots and chatbots. Machine learning is one of the most important areas of Artificial Intelligence. Machine learning provides developing methods that can automatically detect patterns in data and then use the uncovered patterns to predict future data. It can be applied across many industries to increase profits, reduce costs, and improve customer experiences. In this course I'm going to provide you with a comprehensive introduction to the field of machine learning. You will learn how to build predictive models by extracting patterns from large datasets. These models are used in predictive data analytics applications including price prediction, risk assessment, predicting customer behavior, and document classification. Also i'm going to offer you a detailed and focused treatment of the most important machine learning approaches used in predictive data analytics. You'll discover how to make informed decisions about which algorithms to use, and how to apply them to real-world scenarios. In addition you'll learn how to drive innovation by combining data, technology and design to solve real problems at an enterprise scale. This course is focused on helping you drive concrete business decisions through applications of artificial intelligence and machine learning. It makes the fundamentals and algorithms of machine learning accessible to students in statistics, computer science, mathematics, and engineering. This means plain-English explanations and no coding experience required. This is the best practical guide for business leaders looking to get true value from the adoption of machine learning technology.Who this course is for:

• Developers
• Technology consultants
• Engineers
• Computer scientists
• Statisticians

This specialization is made for people working with data (either small or big). If you are a Data Analyst, Data Scientist, Data Engineer or Data Architect (or you want to become one) " don't miss the opportunity to expand your knowledge and skills in the field of data engineering and data analysis on the large scale.In four concise courses you will learn the basics of Hadoop, MapReduce, Spark, methods of offline data processing for warehousing, real-time data processing and large-scale machine learning. And Capstone project for you to build and deploy your own Big Data Service (make your portfolio even more competitive).Over the course of the specialization, you will complete progressively harder programming assignments (mostly in Python). Make sure, you have some experience in it. This course will master your skills in designing solutions for common Big Data tasks:- creating batch and real-time data processing pipelines,- doing machine learning at scale,- deploying machine learning mo