Learn how to use Python for data science from Edvancer.Julia Normally, data geeks use one programming language (like R, Python, etc.) to prototype a predictive model and another programming language (like C, C++) to make the model faster. You need to learn two or three programming languages, write a significant amount of code and switch between different code editors and source files to deploy a working predictive model. This is a cumbersome task, and takes more time than any data scientist can afford to waste. In Julia, you can write code with the performance of C so that you don’t have to rewrite its code in a low-level language (like C, C++). Julia’s only drawback at this point is a dearth of libraries – but Julia makes it easy to interface with existing C libraries. I encourage you to download Julia and use it, it has an active and supportive community. Hadoop Hadoop platform was designed to solve problems where you have a lot of complex data sets that doesn’t fit into a traditional relational database. Hadoop is a distributed file system (HDFS) — with multiple nodes/servers– that helps businesses store unstructured data in vast volumes, at speed and on commodity hardware, at a very low cost. HDFS uses a programming model called Map Reduce to access and analyze the data in it. Map reduce process all the data on all the nodes.