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

I love my new job!

“My boss encouraged me to take the training and now I’m really glad I did because I’m now doing data analytics work full time.” L.L.

Superb way to learn

“I really enjoyed the online/modular format of this course. The material was presented clearly and concisely and allowed me to focus longer on concepts that were difficult, while glancing over concepts I was already familiar with.” A.C.

This is how I like to learn

“This is how I like to learn, at my own pace. I like the bite-sized tutorials and I feel a real sense of accomplishment when I complete the exercises that follow them.” M.J.

Great training!

“I watched videos, read short tutorials, viewed examples, ran demo programs, and then performed exercises that demonstrated my comprehension of the subject matter.” S.L.

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.

The program is great

“I cannot compliment enough any training that involves students actually working on the problems rather than just listening.” A. S.