Training Success Elements
- You learn on your own schedule, not on someone else’s schedule
- Exercises build competency, confidence, and a feeling of accomplishment
- Realtime AI-based contextual assistance is available, whenever needed
- You are assigned a personal instructor
- You are fully qualified and job-ready, when you graduate
Overview of Training
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.
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More Information
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