Overview of Data Analytics Training

Training begins with SQL Fundamentals (80 hours) where trainees 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. Trainees 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 trainees 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 trainees have little or no prior experience in computer programming, then they begin with Introduction to Computer Programming (80 hours). This powerful visual course transforms the way they think. In computer programming, correct algorithmic (computational) thinking is way more important than the knowledge of a particular programming language. This course unlocks their computer programming potential, and make it much easier for them to learn Python and other programming languages.

If trainees have sufficient prior experience in computer programming, they 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 them 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, trainees need to perform a Capstone Project (40 hours) under the supervision of an NCLab instructor in order to graduate and obtain a college-provided 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 trainees are fully qualified to apply for Data Analyst job openings.

What Our Trainees Say About Us

The training is really great!

“Not easy but really informative. Practical experience was what I wanted and I feel that I got it.” F.Z.

Compliments to the NCLab team

“Please extend my compliments to the NCLab team if you can, and keep advocating for this type of learning, if at the very least as an option for people like me who learn well this way.” F. A.