TOOLS YOU WILL LEARN
Data analysts must know how to work with R which is not only the most popular programming language used for data analysis but also an indispensable IT skill.
Once you have covered the nuances of R, you will learn the intricacies of working with data through wrangling and visualizing them
Any aspiring data analyst should have good grasp over statistics as it’s impossible to work with data otherwise. It’s crucial to know how to employ statistical analysis while collecting, organizing and analyzing data so that insightful interpretations can be derived.
Regression models play an integral role in data-driven decision making for any analyst. This unit will emphasize on all about modeling in R.
Algorithms can determine interesting patterns from large datasets during data mining. Having a deep understanding of how these algorithms work and ways to use them effectively is necessary during data analysis.
Time series forecasting helps analysts to make business forecasts based on historical data patterns. This aids in shaping future business goals and predicting market behavior.
Transforming data into actionable information using SQL and Excel will help extract information required to effectively transform data into actionable information.
Simple visualization makes it easy to represent even the most complicated datasets. Tools like Tableau can aid in this process.
The course culminates in an enterprise-level project for a fictitious client that will expose you to every stage of the data analytics process. Every student is guided by industry experts as they bring their personal projects to life. Alternately, students may choose to work on a live project from their organization. Our students generally come from varying backgrounds. We encourage all our students to pursue projects that are best suited for their careers and domains. The project is an opportunity for you to test your skills and demonstrate your ability to invent solutions for real world problems