Taught by the industry experts. You can achieve your career goals with our comprehensive Data Analytics Bootcamp where business data analysis, data mapping, collections and structuring data keeps your company up-to-date with growth and expansion.
Start date: Oct 12th, 2021
The program will be 100% online
Critical thinkers create an environment for businesses to flourish. Our Data Analytics Program is designed for working Professionals who have a knack for being able to organize and assess relevant data. You will learn data analytics techniques and design processes to improve the flow of information and decision-making within an organization while providing insights to business leaders who make high-impact business decisions. Possessing a desire to troubleshoot data problems is essential in today’s digital age.
A modern introduction to probability develops a foundation for understanding statistics, randomness, and uncertainty. A variety of real-world explanations are provided in this course to help the student understand how probability is deeply intertwined with data.
The performance of randomized algorithms make random choices and are more efficient than any current deterministic applied method.
The worlds of medicine, finance, computer science, meteorology and biology make use of conjectures and observed as well as unobserved problems.
Python is a great language for doing data analysis, primarily because of the fantastic ecosystem of data-centric Python packages.
Python is also a great beginner’s programming language, and more versatile than R, which is more oriented to data sciences. It covers multiple tasks, including web development, machine learning, and data science, among other tasks. Its outstanding reputation comes from how concise and easy to read it is.
With access to a vast number of R packages and high performance, R has gained high popularity among statisticians. In the field of statistical analysis, R allows analysis and cleaning of data which proves useful for companies. With R performing equally well in visualizations, it makes it easy to create different plots and determine various trends in data.
Machine learners also use R in implementing algorithms. R is useful in predictive analysis and when building various models including linear regression, decision trees or classification models.
With the digital transformation of our world and increasing competition, companies need to make wise decisions; here the field of data science comes into play. Lauded as one of the most trending fields with exceptional growth, data analysis makes use of various scientific methods and techniques to analyze data and find different hidden patterns. Here, R programming is a powerful language that allows data analysts to perform their tasks efficiently with high performance by performing statistical analysis, creating visualizations and building predictive models.
The Tableau platform is a data analytics program used for business management and intelligence. Compared to other data analytics programs that require a programming background, Tableau provides a user-friendly interface that anyone can use.
Tableau can connect and prepare your data, no matter the size or file format. Furthermore, the program translates data files, whether cloud-based, on-premises, or flat. Tableau features hybrid connectivity, which covers live data analysis and in-memory data analysis from encrypted sources.
Tableau Prep, a product of the Tableau suite, offers a smooth visual interpretation of data.
Another boon of the Tableau suite is its ability to understand data more efficiently. Tableau offers a seamless environment that is more interactive than the normal stop-and-go process of data reporting.
Power BI is a collection of software services, apps, and connectors that work together to turn your unrelated sources of data into coherent, visually immersive, and interactive insights. Your data may be an Excel spreadsheet, or a collection of cloud-based and on-premises hybrid data warehouses.
SQL, or Structured Query Language, is a programming language intended for relational data management. Relational data management pertains to databases that are related to each other. Relational databases often present themselves in tables. Relational database management is how you create, administer, and update relational databases. If you wish to be data-literate, SQL is the language to learn.
Excel is a great tool for analyzing data. It’s especially handy for making data analysis available to the average person at your organization. Other than great flexibility, superior number crunching powers and easy access MS Excel also provide its users many benefits including;
Git is a DevOps tool used for source code management. It is a free and open-source version control system used to handle small to very large projects efficiently. Git tracks changes in source code, enabling multiple developers and testers to work together on non-linear development.
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