Training Overview

Data Analytics can’t be learned in a few weeks by passively watching video tutorials and doing unassisted assignments. It’s an advanced skill set which can only be mastered with a significant amount of closely supervised practice. NCLab’s proven training method is called Instructor-Assisted Learning By Doing and it closely parallels an unpaid apprenticeship.

Throughout trainees’ learning, they are assisted by an engaging Artificial Intelligence-based teaching platform that watches their every step, grading their work in real time, and helping them with contextual information, hints, and templates, as needed. The AI-based platform also teaches them established best practices, methodologies, and guidelines that professionals follow to ensure consistency, accuracy, and reliability in their work. 

Trainees learn actively from Day 1. After gaining confidence in one topic, they move to the next one. The progression has been improved and tuned for many years and it is so smooth that they never get lost and they are never alone. 

Our highly responsive instructional support team composed of professional Data Analysts, college instructors, and former NCLab trainees stands by to promptly assist them with the coursework when needed. Trainees are each assigned a personal coach who prepares a personalized roadmap and training timeline with them, and then works with them on a weekly basis for the entire duration of the training. 

The entire Data Analyst career training program takes approximately 320 hands-on hours and it provides trainees with enough Data Analytics practice to make them highly skilled and enough theoretical knowledge to pass the CompTIA Data+ industry-recognized certification exam. 

Coursework

To begin with, given that Data Analysts work extensively with numbers, they must know some math. If in consultation with their coach, it is determined that enrollees need a basic middle school level math refresher, our optional Workplace Math course provides hands-on review and practice to bring them up to speed.

With an appropriate math foundation in place, they begin their Data Analyst training with comprehensive college-level data analytics courses, in which you learn all about:

• Data sources
• Data types
• Data relationships
• Data structures
• Sorting, filtering and grouping, data and
• Other fundamental techniques of Data Analytics.

They learn basic and advanced spreadsheet operations, including data visualization and analytics, using Google Sheets. They learn how to create interactive dashboards and reports. They also learn the fundamentals of data mining, statistical methods, data analysis, and data visualization. Finally, they learn about data governance, quality, and controls. Upon completing this course, they understand how data is acquired, stored, manipulated, analyzed, and used to make better business decisions.

They continue their training with an SQL Fundamentals course where they 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. They learn how RDBMSs work, how to make basic queries, how to do extracts, how to use aggregate functions, how to 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. This course teaches trainees how to use conditional expressions, how to work with text including search-and-replace operations, how to formulate subqueries and advanced joins, and how to define and use SQL functions.

The last course is CompTIA Data+ Prep which prepares trainees for the CompTIA’s Data+ exam, an industry-recognized certification.

Finally, trainees do a capstone project, which is a hands-on project where they conduct queries. All queries are conducted in a relational database system and a suitable editor that individual trainees choose and install on their personal computer. They write and execute queries to clean and group data and obtain descriptive statistics of the data and create visualizations of their choice.

Program Syllabus

We invite you to look at the training program syllabus. It is very different than other syllabi you might have or will look at because while all syllabi show you what is taught in the training, our syllabus shows you both what trainees are taught and what they are required to make use of themselves. To you, this means that employees taking the training have actually mastered each of the topics covered.

Click here to access the syllabus and use the links in the table of contents to see how the various topics that trainees are required to master.

Advanced Data Analyst Training

Upon completing the Data Analytics training, graduates can continue by taking a follow-up Advanced Data Analyst training program that makes them Python Data Analysts. This program includes an optional Introduction To Programming course for trainees who have no prior experience with computer programming, a Python Fundamentals course, a full complement of Python topics, and a Capstone Project. More information about this training program is available upon request.

Developing Soft Skills

At the same time as trainees develop Data Analytics hard skills, coaches develop their soft skills. Those include professional communication, attention to detail, time management, critical and logical thinking, problem solving, perseverance, and adaptability, among others.

Experience NCLab’s Learn-By-Doing — You’ll Love It.

Click here to see how NCLab’s AI-based teaching platform is with trainees throughout their training, helping them do mini projects in realtime and providing them a feeling of accomplishment as they complete each mini project.

Get More Information

To talk with one of our product specialists about what this training program could do for your enterprise, schedule a call below, fill in the Get-In-Touch form, or simply use the CHAT BOX at the bottom right of this screen.

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