The Data Science with R and Python is an entirely revolutionary course that requires the inexperienced students from novice employees to capable job-ready professionals in this highly competitive sector. This course is being designed by world class pros and has been extensively tested by experienced professionals. The courses have been designed as an accelerated curriculum, and they are designed keeping in view the requirements of those pupils who have little or no opportunity to complete a full-fledged academic program. They're very flexible and easily adaptable to the hectic working program, and allow the students to complete the entire course within the stipulated time-frame.

These Data Science Courses provide the essential knowledge to conduct a data-driven business successfully. The course consists of four modules: Data Structures, Introduction to R, Introduction to Python, Data Mining.

Each module covers a different element of Data science, as well as also the modules are interspersed to produce a comprehensive syllabus that includes both theoretical and practical aspects. Each module is designed in such a manner in which the students may grasp the basic concepts of the subject and learn them without going through a hefty theoretical lecture.

Pupils will also learn the fundamentals of programming, in a style that is similar to the way they will learn R in Data Science Course II. This is only because the pupils need to get a firm foundation of computer science, mathematics and fundamental programming to comprehend the concepts of data science. Also, the modules include hands on assignments where the pupil will be able to work on a problem that he or she believes is of great interest to the pupil.

With the program, the student has a opportunity to learn about some of the most advanced theories within the business of information science. The modules cover a vast array of topics such as distributed databases, optimization of systems, optimization of algorithms, statistical methods, statistical inference and much more.


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