Research and Development of Advanced Technologies such as Machine Learning, Artificial Intelligence, Big Data Analytics, Data Science, Block chain Technologies and all other advance technologies.
Machine learning is a form of artificial intelligence where the focus is to develop computer programs that automate data analysis by learning and adapting through the experience without the need for precise programming. Our course has been designed to help you master machine learning concepts and techniques, working with actual data, developing algorithms through supervised and unsupervised learning, performing classification and regression operations and constructing time series models. This course explores in depth the libraries and functionalities the python programming language offers for machine learning techniques in order to draw conclusions from data. The course includes 2 projects to solidify your knowledge and skills you’ve gained.
This rigorous program is designed to give in-depth knowledge of the skills required for a successful career in ML/AI. The program is a combination of Data Science, Machine Learning, Deep Learning, and Artificial Intelligence and is designed to give you a solid understanding of advanced tools, their usage, and models.
Specifically, this program is aligned with the following learning objectives:
Understanding data structure and data manipulation in-depth
Learning to perform scientific and technical computing by using Scipy and its sub-packages including Optimize, IO, Statistics, and Weave
Mastering mathematical computing using Numpy and Scikit-Learn packages
Understanding the concepts of supervised and unsupervised learning models together with TensorFlow, its functions, the operations, and execution
A detailed look at applying machine learning in order to process large natural language data
Deep diving into new applications of computer vision techniques through deep learning, including face recognition among others.
The concept of big data has been around for years; most organizations now understand that if they capture all the data that streams into their businesses, they can apply analytics and get significant value from it. But even in the 1950s, decades before anyone uttered the term “big data” businesses were using basic analytics (essentially numbers in a spreadsheet that were manually examined) to uncover insights and trends.
The new benefits that big data analytics brings to the table, however, are speed and efficiency. Whereas a few years ago a business would have gathered information, run analytics and unearthed information that could be used for future decisions, today that business can identify insights for immediate decisions. The ability to work faster – and stay agile – gives organizations a competitive edge they didn’t have before.
Why are big data analytics important?
Big data analytics helps organizations harness their data and use it to identify new opportunities. That, in turn, leads to smarter business moves, more efficient operations, higher profits and happier customers. In his report Big Data in Big Companies, IIA Director of Research Tom Davenport interviewed more than 50 businesses to understand how they used big data. He found they got value in the following ways:
Cost reduction. Big data technologies such as Hadoop and cloud-based analytics bring significant cost advantages when it comes to storing large amounts of data – plus they can identify more efficient ways of doing business.
Faster, better decision making. With the speed of Hadoop and in-memory analytics, combined with the ability to analyze new sources of data, businesses are able to analyze information immediately – and make decisions based on what they’ve learned.
New products and services. With the ability to gauge customer needs and satisfaction through analytics comes the power to give customers what they want. Davenport points out that with big data analytics, more companies are creating new products to meet customers’ needs.
Data Science is an advanced technology that makes use of robust techniques and methodologies to analyze large volumes of Big Data. The deep data insights that are extracted from the Big Data will help the enterprises to make effective business decisions. Data Science has now become a major necessity for businesses, irrespective of its size. In the present age of Big Data, to stay competitive, enterprises need to efficiently develop and implement Data Science capabilities or risk being left behind.
Why Analytics Path For Data Science Training?
‘RKITS R&D Lab’ offers integrated program in Data Science Training In Hyderabad in collaboration with real-time industry experts in Data Science. This advanced Data Science Training program comprises of ‘6 different trainers’ who are carefully handpicked from the analytics industry. Our training experts are mostly from IIT & IIM background. They are also having many years worth experience of working in Data Science, AI, Machine Learning and Deep Learning & Business Analytics industries. This Data Science Course helps in shaping your dream of becoming a successful Data Scientist into a reality.
Introduce you to the concepts of Block chain and its platforms – Bitcoin, Ethereum, Hyper ledger and Multi Chain. The course provides an overview of the structure and mechanism of Block chain. You will learn about the Ethereum ecosystem, how smart contracts are developed using Solidity and how to deploy a business network using the Hyper ledger Compose.