Training Success Elements

  • Hundreds of AI-mentored mini projects build your competency and confidence and give you a feeling of accomplishment.
  • Realtime AI-based contextual assistance is available, whenever needed.
  • You get personal academic advice and instructional support throughout your training.
  • You never miss training sessions because of family and work responsibilities.
  • You are fully qualified and job-ready, when you graduate.

Overview of Training

This gold star training program is designed for you, if you are determined to become a skilled Data Analyst. It provides you with enough practice and theoretical knowledge to make you job-ready when you graduate. It also teaches you the soft skills that employers look for in job applicants. Upon completing the training, you are ready to start a successful new career as a Data Analyst.

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.

Throughout you learning, you are assisted by a powerful Artificial Intelligence-based teaching platform that watches your every step, grading your work in real time, and helping you with contextual information, hints, and templates, as needed. The AI-based platform also teaches you established best practices, methodologies, and guidelines that you need to follow to ensure consistency, accuracy, and reliability in your work.

You learn actively from Day 1. After gaining confidence in one topic, you move to the next one. The progression has been improved and tuned for many years and it is so smooth that you never get lost and you 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 you with the coursework when needed. You are assigned a personal academic advisor who prepares a personalized roadmap and training timeline with you, and then works with you for the entire duration of the training. Because your training is self-paced and individualized to your schedule, you are able to build a consistent training routine with your academic advisor that does not interfere with your work and family commitments.

The entire Data Analyst career training program takes approximately 320 hands-on hours.

Coursework

To begin with, given that Data Analysts work extensively with numbers, you must know some math. If, in consultation with your academic advisor, it is determined that you need a basic middle school level math refresher, our optional Workplace Math course provides hands-on review and practice to bring you up to speed. In small and simple steps, we review how to work with whole and decimal numbers, fractions, percentages, proportions, simple and compound interest, unit conversions, and solve simple workplace-related math problems. The course includes several ACT WorkKeys Applied Math practice exams. After completing this course, you are ready to take the ACT WorkKeys Applied Math exam, which is highly valued by employers.

With an appropriate math foundation in place, you begin your Data Analyst training with comprehensive data literacy 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.

You learn basic and advanced spreadsheet operations using Google Sheets. You also learn the fundamentals of data visualization, statistical methods, data analysis, and data mining. Finally, you learn how to create interactive dashboards and reports. Upon completing this course, you understand how data is acquired, stored, manipulated, analyzed, presented, and used to make better business decisions.

You continue your Data Analyst training with an SQL Fundamentals course, where you 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. You 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 you 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 you for the CompTIA's Data+ exam, an industry-recognized certification, which adds a significant weight to your resume.

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

Program Syllabus

We invite you to look at our training program syllabus but we need to explain how it is different from other syllabi you might have or will look at.

While all syllabi show you what is taught in the training, our syllabus shows you both what you are taught and what you are required to make use of yourself. To an employer, this means that you 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 you will be expected to master.

Advanced Data Analyst Training

Upon completing the Data Analyst Training, you can either get a job as a Data Analyst or continue by taking a follow-up Advanced Data Analyst training program that makes you a job-ready Python Data Analyst. 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 is available upon request.

Developing Soft Skills

At the same time as you develop Data Analyst (hard) skills, you also develop soft skills during your academic advice sessions and during your communications with your instructional support team that employers put a major emphasis on. These 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 you throughout your training, helping you do mini projects in realtime and providing you a feeling of accomplishment as you complete each mini project.

 

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.

I love going to work every day!

“Thank you for giving me the competency and confidence that I needed to get a dream job. With my limited formal education, I had serious doubts that I could master SQL and Python but learning by doing worked perfectly.” G.K.

Perfect teaching method

“As an adult with a busy schedule and the need to work around banking business hours etc.: this method of teaching is perfect for me and I would recommend it for basically anyone on any subject.” F. V.

Superb way to learn

“I really enjoyed the self-paced format of this training program. 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.

I really learned a lot

“I really learned a lot and have found a new passion towards data science and analytics I didn’t know I had.” M.N.

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.

Totally worth it

“I just completed 3 courses: SQL Fundamentals, Advanced SQL, and Predictive Data Analytics with Python within the estimated hours that they had advised. It was a lot of work, but totally worth it!” Q.B

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.

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.

You do a great job explaining the concepts

“So far I’m enjoying the course. You do a great job explaining the concepts and the logic behind each step (the explanation for the difference between WHERE and HAVING comes to mind)!” R. C.

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.

I am thoroughly enjoying the training

“I feel like I am learning a skill, much more than I felt in other courses. The use of repetition, doing programming in pieces, and the entire way the platform is laid out are far superior to how my university teaches their main, introductory, programming courses. It is too bad that the philosophy of academia is standing in its own way.” K.L.

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