Overview of Data Analytics Training

This training program consists of 4 or 5 courses, depending on whether or not trainees have prior programming experience. Each course must be completed within 6 months of its start date, but it can be completed much sooner if a trainee works hard. This career training program is completely self-paced and allows trainees the flexibility to study as much or as little as their schedule allows — they set their own pace and finish on their own timeline.

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 sufficient prior experience in computer programming, they go directly to Introduction to Python for Data Science (80 hours), an introductory Python programming course where they learn in a hands-on fashion to solve programming tasks of gradually increasing complexity, ranging from simple calculations, working with text strings, loops, conditions, and variables, to file operations and data visualization.

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 essential. This course unlocks their computer programming potential, and makes it much easier for them to learn Python and eventually other programming languages in the future.

The last course in the sequence is Predictive Data Analytics with Python (80 hours). In this course trainees learn 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. At the end of this course, they complete a Capstone Project under the supervision of a senior NCLab Data Analytics 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 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.