Program in Data Science
In this era of Data trade, with the recent boom in the data industry, data scientist has become a glammed up term familiar for every data oriented Industry. Data Science is a much broader concept where a set of tools and techniques are implied upon to extract the insights from the data. It involves several aspects of mathematics, statistics, scientific methods, Machine Learning etc. to drive the essential analysis of data. Because companies are starting to understand what kind of value Data Scientists can bring to their business, the demand for these profiles is going up. They are automating tasks, delivering deeper insights and uncovering new business opportunities.
Why in Demand?
The demand for data scientists is increasing so quickly,that McKinsey predicts that by 2020, there will be a 60 percent gap in the supply of data scientists versus demand.
The fastest-growing roles are Data Scientists and Advanced Analysts, which are projected to see demand spike by 28% by 2020.
About the Course
This is a complete Data Science through a rigorous curriculum developed by the world’s topmost experts in the field, the program covers both the foundations of data sciences, along with applied methods useful in practice. So, Students will learn how to collect, prepare, store, analyze, and visualize data, all at large scales as this course is a blend of data science being applied alongwith the detailed substitutes such as R, Python, Machine Learning, Hadoop, Hive, AI, Deep learning, Tableau, Data extraction, wrangling and many more data analytics tools.
What you’ll Learn
- Introduction and importance
- Data acquisition and Data Science lifecycle
- Experimentation, evaluation and project deployment tools
- Different algorithms used
- Predictive analytics and segmentation using clustering
- Big Data fundamentals and Hadoop integration with R
- Data Scientist roles and responsibilities
- Deploying recommended systems on real-world data sets
- Work on data mining, data structures and data manipulation.
What does a Data Scientist do?
- Collect Enough Data- As it implies, a Data Scientist has to collect enough data in order to make sense of the problem at hand and get a better grip of the issue with respect to the time, money and resources needed.
- Process the Raw Data- Data can rarely be used in its original form. It needs to be processed, and there exist various methods to convert it into a usable format.
- Explore the Data- After the data has been processed and converted into a form that can then be used in the later stages, the Data Scientist need to explore it further so as to get the characteristics of the data and find out more about the obvious trends, correlation and more.
- Analyze the Data- The Data Scientist deploys various arsenals in his repository like statistics and probability, linear and logistic regression, time-series analysis and more in order to make sense of the data.
- Communicate the Results- At the end of the entire process, there is a need to communicate the findings to the right stakeholders in order to get the groundwork done for all recognized issues.
- Data Scientist
- Data Analysts
- Machine Learning Engineer
- Database Administrator
- Data Architect
- Data & Analytics Manager
No Reviews found for this course.