Training Details

 

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

Training begins with SQL Fundamentals (80 hours) 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 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 you 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 you have sufficient prior experience in computer programming, you go directly to Introduction to Python for Data Science (80 hours), an introductory Python programming course where you learn in a hands-on fashion by solving 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 you have little or no prior experience in computer programming, then you begin with Introduction to Computer Programming (80 hours). This powerful visual course transforms the way you think. In computer programming, correct algorithmic (computational) thinking is essential. This course unlocks your computer programming potential, and makes it much easier for you 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 you 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, you 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 you are fully qualified to apply for Data Analyst job openings.

SQL Fundamentals
Skills Learned:
  • RDBMS and SQL
  • Write basic queries
  • Order and filter data
  • Combine multiple conditions
  • Group results
  • Use aggregate functions
  • Create and manage tables
  • Insert and delete data
  • Join tables
Read More
Advanced SQL
Skills Learned:
  • Conditional expressions
  • SQL errors
  • Text operations
  • Search-and-replace
  • Sets, relations, bags
  • Subqueries
  • Advanced joins
  • Functions
  • Data types
Read More
Predictive Data Analytics with Python
Skills Learned:
  • Import data from CSV files
  • Work with data frames
  • Clean and manipulate data
  • Visualize and present data
  • Simple linear regression
  • Multiple linear regression
  • Logistic regression
Read More
Intro to Python for Data Science
Skills Learned:
  • Using Python for calculations
  • Text strings and regular expressions
  • Tuples, lists and dictionaries
  • Python libraries
  • Working with files
  • Data visualization
Read More

What Our Trainees Say About Us

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.

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.

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.

It’s working well

“It might sound weird, but I feel as though it teaches the right parts for Python. When I was learning Python before, there were a lot of steps that felt skipped but are explained now.” P.T.

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.

I love it!

“I feel like I am actually LEARNING how to program, and the chunking method of the material is wonderful.” D.A.

Yes!!

“I am really enjoying this course and learning python and I also like the way that it teaches the material. I’m very glad I took this course!” R. B.

Large amount of Python programming practice

“I really enjoyed and found the Python Fundamentals and Advanced Python courses incredibly useful. In fact, the large amount of Python programming practice questions in both courses helped me obtain my summer software development internship at Pfizer by preparing me for a variety of programming interview questions.” F. F.