Overview of Training
Please spend some time looking closer at our course syllabuses and who we are. We are proud of the fact that we have been doing Learn-by-doing training for ten years. We believe that the more you look at our Data Analytics Career Training program, the more you will be excited about the bright future that is in front of you.
Training begins with SQL Fundamentals (80 hours) where you learn about data and databases, with emphasis on Relational Database Management Systems (RDBMSs), which are used in virtually all industries and organizations to store data about employees, products, services, inventory, financial transactions, etc. You learn how a RDBMS works, how to make basic queries, use aggregate functions, create and manage tables, and how to use basic joins.
In a real company setting, RDBMSs tend to be large, complex, and messy (they often contain damaged and/or incomplete data). To successfully handle such databases, training continues with Advanced SQL (80 hours). This course teaches you how to use conditional expressions, work with text including search-and-replace operations, formulate subqueries and advanced joins, and how to use SQL functions.
The next part of the Data Analyst Career Training Program includes Python programming. Python is a step up from SQL. If you have little or no prior experience in computer programming, then you will begin with Introduction to Computer Programming (80 hours). This powerful visual course will transform the way you think. In computer programming, correct algorithmic (computational) thinking is way more important than the knowledge of a particular programming language. This course will unlock your computer programming potential, and make it much easier for you to learn Python and other programming languages in the future.
If you already have sufficient experience in computer programming, you will progress directly to Predictive Data Analytics with Python (80 hours) which starts by covering a necessary minimum of the Python programming language for applications in Data Science. Then it teaches you how to use Python and its powerful free libraries including Pandas, Numpy, Scipy, Matplotlib, Seaborn, and Statsmodels to read data from files, clean data, present data in visual form, perform qualitative and quantitative analysis of data, interpret data, and make predictions.
After completing the required coursework, you will need to perform a Capstone Project (40 hours) under the supervision of an NCLab instructor in order to graduate and obtain a career certificate.
Syllabuses
Following are detailed syllabuses for each course in the Data Analytics Career Training program. The level of detail covered in each of the self-paced interactive courses ensures that you are fully qualified to apply for Data Analyst job openings.
Accelerate your career and create a better life ahead.
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Please look at our Tuition and Enrollment pages.