Quick Stats
Analytics industry is a volatile industry and picks up fast on technology. We have seen an upward trend for R and Python as a skill set in combination with SAS as a tool & Certification
The universities and the start-ups are adapting to R and Python. Hence a huge scope in research-oriented jobs as a practitioner.
There is a dearth of data scientist across the globe where R & Python as a skill set is picking up fast to fill up the gap. Early entries will scoop big is the prediction of the Data Pundits
Benefits
R +Python as a tool
R as a tool is the major component of today's data science. Python training along with fills the gap for the machine and deep learning. This is an added upskill in the skill list and will help you up the success ladder
Project Driven approach
There will be no run through ppt and decks as we don't believe in such methods of learning and spreading education. It would be hands-on and classes would actually be workshops with more focus on the application part
R-Data Science Python -Machine Learning
Data Scientists are betting heavy on R as a soul ingredient for data science. Machine Learning is in these days for Python. The world is moving away from contemporary languages to data-driven languages and R, Python is holding a good place as far as data science is concerned.
Who Should Attend
- Final Year Students who are looking for research-oriented jobs curriculum abroad
- Freshers out of the campus who are looking for jobs in start-ups
- Experienced folks who are in the data industry and look forward to adapting R, Python
- Experienced professionals who look forward to switching the jobs/domain to data science & Machine Learning
Course Outcome
- Understand the outlining features of R, Python
- Strong foundation with more hold on basics
- Data Extraction and Analysis with Machine Learning
- In-depth knowledge of R & Python as a tool and the applied language
- Proper application as to where and where not to apply
Curriculum
FAQS
Is this a classroom programme
Yes it is
what is python?
Python is an open-source, free to use programming language used in different industries, predominantly in the data industry and development field. Though it is just a programming language, but it can do wonders if you know how to use it with other tools and languages. The best thing about python is that it has lots of inbuilt functions which you don’t have to write every time if you’re working on python. You just have to invoke the appropriate library to make use of any function. While doing statistical analysis, python comes in hand as it has the required functions, and there’s no need to write lengthy and time-consuming functions. Data scientists generally prefer this language over other languages as it can be used in a variety of tasks, be it Machine learning, deep learning or NLP (Natural Language Processing). While learning python, one thing that should be kept in mind that python alone is not sufficient to be a data scientist. It would be best if you learned different tools such as SQL, Tableau or Power BI, or Big Data techniques to work as a data analyst or scientist. But one should not forget to learn the concepts as well, which are applied to python or on anything to perform the analysis. Hence we prefer to undergo python training from a reputed institution that can make you learn this language.
What is data science in simple words?
This can be understood very easily by differentiating the two words used above, Data and Science. Knowing and doing anything or everything with data is what data science is. Getting meaningful insights from raw data, making decisions is where data science is used. It has many pillars covering data analytics, machine learning (ML), deep learning (DL), natural language processing (NLP), Artificial intelligence (AI), and Big Data and a lot of other things.The core of data science is Statistics and Mathematics. While analyzing any data, one needs to build a model using statistical concepts and have to apply that model on any programming language such as Python or R.It may or may not require visualization tools to represent data and certain deployment concepts of ML, DL, or NLP. A data scientist is the one who knows all the above ideas and the several tools used in the project life cycle.
How Data Science Training Help to Get a Good Job?
There was a time when everybody wanted to be a software developer, but now the time has changed. Now due the supply and demand, there is a surplus of engineers in the industry, and now people are moving towards automation and artificial intelligence to reduce the human error and cost factor. And there is stagnation in the other sector too. So, if you’re looking for a good career, then going into the data industry seems to be the best possible shot.But it is impossible to get into this industry without having the relevant skills required. Though there is not any background necessary to enter into this field, one should have the desired knowledge before entering into it. This is where data science training comes in the picture. Anyone can be a data scientist provided that he/she has the required skills that involve statistics, mathematics as concepts and tools such as python, SQL, Power BI, etc. In the end, if you’re aspiring to become a data scientist then start getting some training in it, that’s the only option.