Thedemand forBig Data Hadoop Developers, Architects, Data Scientists, Machine Learning Engineers is increasing day by day and one of the main reason is that companies are more keen these daysto get more accurate predictions & forecasting result using data. They want to make sense of data and wants to provide 360 view of customers thereby providing better customer experience. This course is designed in such a way that youwill get an understanding of best of both worlds i.e. both Hadoop as well as Data Science. Youwill not only be able to perform Hadoop related operations to gather data from the source directly but also they can perform Data Science specific tasks and build model on the data collected. Also, youwill be able to dotransformations usingHadoop Ecosystem tools. So in a nutshell, this course will help the students to learn both Hadoop and Data Science Natural Language Processing in one course. Companies likeGoogle, Amazon, Facebook, Ebay, LinkedIn, Twitter, and Yahoo! are using Hadoop on a larger scale these days and more and more companies havealready started adopting these digital technologies. If we talk about Text Analytics, there are several applications of Text Analytics (given below) and hence companies prefer to have both of theseskillsetin theprofessionals. One of the application of text classification is afaster emergency response system can be developedby classifyingpanic conversation on social media. Another application is automating the classification of users into cohorts so that marketerscan monitor and classify users based on how they are talking about products, services or brands online. Content or product tagging using categories as a way to improve browsing experience or to identify related content on the website. Platforms such asnews agencies, directories,E-commerce, blogs, content curators, and likes can use automated technologies to classify and tag content and products. Companies these daysare leaning towardscandidates who are equipped with best of both worlds and this course will proved to be a very goodstarting point. This course covers complete pipeline of modern day ELT (Extract, Load and Transform) and Analytics as shown below: Get data from Source -> Load data into Structured/Semi Structured/Unstructured form -> Perform Transformations-> Pre-processthe Data further -> Build the Data Science Model -> Visualize the ResultsLearn and get started withthe popular Hadoop Ecosystem technologies as well one the most of the most hot topics in Data Sciencecalled Natural Language Processing. In this course you will: Do Hadoop Installation using Hortonworks Sandbox. You will also get an opportunity todo some hands-on withHadoop operationsas well as Hadoop Management Service called Amabri on your computer. Perform HDFS operations to work with continuous stream of data. Install SSH and File Transfer related tools which helps in operational activities of Hadoop. Perform NIFI installation and develop complete workflow on Web UI to move the data from source to destination. Also, perform transformations on this data using NIFI processors. Spin up Apache Solr which allows full text search and also to receive text for performing Real Time Text Analysis. Engage Banana Dashboard to visualize Real Time Analytics on streaming data. Store the Real Time streaming JSONdata in structured form using Hive Tables as well as in flat file format in HDFS. Visualize the data in the form of Charts, Histograms using Apache Zappelin. Learn the Building blocks of Natural Language Processing to develop Text Analytics Skills. Unleash the Machine Learning capabilities using Data Science Natural LanguageProcessing and build a Machine Learning Model to classify Text Data.
