Training Success Elements

  • Trainees develop an entirely new set of hard and soft skills.
  • Trainees never miss training sessions because the training is self-paced.
  • Exercises will build competency and confidence, and provide trainees a feeling of accomplishment.
  • Realtime AI-based contextual assistance will always be there, helping you.
  • Trainees get personal coaching and tutoring throughout their training.
  • Upon graduation, trainees are positioned to grow in the new automation-based economy.

Overview of Training

This training program is 160 hours in length and is all hands-on learning. The actual time taken to complete the training varies, depending on how many hours trainees’ schedule allows them to allocate to their training.

The training begins with a practice-based course, Computational Literacy I, in which trainees learn how computers think, how they operate, and how to direct them to do work. They use a virtual robot to solve various simple tasks. In this way they learn essential skills such as how to identify repeating patterns and how to break complex problems into simpler ones. 

In the next practice-based course, Data Literacy I, trainees learn about spreadsheets, basic operations with rows and columns, formulas, comparison operators, references, functions, pivot tables, etc. They review basic statistical concepts such as mean, median, mode, min, max, range, percentages, etc. They learn basic data visualization and analytics (line chart, pie chart, bubble chart, scatter plot, bar chart, histogram, waterfall, heat map, geographic map, tree map, stacked chart, Infographic, word cloud), etc. Finally, they learn advanced statistical concepts that include distribution, variance, standard deviation, confidence intervals, correlation, P-value, etc.

At the same time as trainees learn new computational and data hard skills, they develop important soft skills, including the ability to focus, to pay attention to detail, to communicate effectively, to solve problems, to use logic so as to make correct decisions, to plan ahead so as to do it right the first time, to persevere, to learn from failure, and to adapt to changing conditions, among others.

Preparation for a 21st Century Career 

Depending on the 21st century career path trainees want to follow, they are then provided with two of the following additional courses, in order to fully prepare them for their subsequent career training. 

  • In Data Literacy II, trainees learn advanced statistical concepts (simple linear regression, correlation, t-test, Z-score, p-values, chi-squared, hypothesis testing, type 1 and 2 error), practice importing data, creating reports and creating dashboards with Google Sheets and Google Data Studio. They also get introduced to how this is done with Tableau and PowerBI. Finally, they learn data concepts and environments (relational / non-relational databases, data mart, data warehousing, data lake, schema concepts), data types, data structures, data file formats, data mining, data acquisition concepts, data cleaning and profiling, and data governance, quality, and controls. Upon the completion of this course, they are fully ready to take the CompTIA Data+ exam, should they wish to do so.
  • In Computational Literacy II, trainees learn more ways in which computers think, how they operate, and how to direct them to do work. Upon completing the program, they have acquired the mindset and skills needed to successfully deal with automation and intelligent machines.
  • In Visual Introduction to Python, trainees learn Python by programming a virtual robotic turtle. They begin with drawing simple geometric patterns, and soon they’re able to follow lines on the ground and navigate complex mazes with the help of the turtle’s color and distance sensors.
  • In Spatial Literacy, trainees develop strong visual-spatial reasoning skills while actively building 2D and 3D models. They begin with creating simple 2D shapes, learn how to manipulate them in the XY plane, how to extrude them to the 3D space, and soon they make their first 3D designs. Their 3D models are automatically checked by the server, and they receive instant feedback and guidance. At the end of the training program, trainees create a capstone 3D model of your own choice under the supervision of a CAD expert.

Preparation for Data Analyst Training

If trainees’ interest lies in Data Analytics, the two additional courses they take are Computational Literacy II and Data Literacy II, in preparation for our Data Analyst Career Training Program.

Preparation for Python Programmer Training

If trainees’ interest lies in Python Computer Programming, the two additional courses they take are Computational Literacy II and Visual Introduction to Python, in preparation for our Python Developer Career Training Program.

What Our Trainees Say About Us

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.

The program is great

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

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.

I’m really enjoying this class

“The emphasis on working at your own pace removes the stress of a normal class, and I can work around my other classes. NCLab is much better than similar programs, such as DataCamp. Not only do I learn the material, I retain it. Each lesson uses all or most of the previous concepts, which provides additional practice and ensures that you don’t forget the previous material. This is one of the most enjoyable and informative programs I’ve taken.” N. L.




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