Please spend some time looking closer at our course syllabuses, our video showing how training is done, and who we are. We are proud of the fact that we have been doing STEM training for ten years.

Overview of Training

Training begins with SQL Fundamentals (80-120 hours) where students 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. Students 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 (80-120 hours). This course teaches students 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 students have little or no prior experience in computer programming, then they will begin with Introduction to Computer Programming (80-120 hours). This powerful visual course will transform 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 will unlock their computer programming potential, and make it much easier for them to learn Python and other programming languages in the future.

If students have sufficient prior experience in computer programming, students will progress directly to Predictive Data Analytics with Python (80-120 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, they will need to perform a Capstone Project (40-60 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 students are fully qualified to apply for Data Analyst job openings.

Take A Short Tour Of Our NCLab's Learn-By-Doing Approach!


What Our Students 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.

NCLab, The Company Behind Data Analytics Career Training

NCLab was formed in 2010 by Pavel Solin, UNR (University of Nevada, Reno) Mathematics Professor, who started working with K-12 schools to help them prepare students in STEM. To do that, he built a platform that was hands-on practice-based and overlaid Karel programming on top of it as his first product.

  • It taught students programming without the need for STEM-qualified teachers
  • It was self-paced to allow students to progress at their own rate
  • It included verified learning so teachers could see the progress of students

Schools and libraries across Nevada implemented it. Schools in other states and countries followed.

In 2017, Nevada State’s Economic Development Department surveyed companies to identify needed STEM job skills. Data Analytics stood out as a STEM career path needing attention. The State teamed up with TMCC (Truckee Meadows Community College) to get the training in place. NCLab was identified as the partner to deliver the training. NCLab developed a college level Data Analyst career training program and TMCC incorporated the training into its curriculum.

Today, NCLab partners with colleges and universities throughout the U.S. to serve their marketplaces. While NCLab provides all student support activities using subject-matter experts, NCLab and those institutions divide other responsibilities that include promoting the availability of the training, providing career and financial counseling, administering enrollment, and providing each student a career certificate upon completion of the training.

There will never be a better time to start offering these career training programs to your community.

Please take a moment to provide us with your contact information below and we will promptly reach out to you to discuss how, together, we can better serve your community while profitably expanding your college’s STEM career training footprint.