NCLab is pleased to announce three new courses in Data Analytics, designed for adults who are beginning to explore the field. Intro to PostgreSQL builds database query skills, Intro to Python for Data Science builds skills in the Python programming language in preparation for data analytics, and Intro to Predictive Data Analysis uses Python and its extensive libraries to analyze data.
Why People Need to Learn Data Analytics
The production line needs a maintenance schedule based on sensor data.
Our parent company launched the Wasabi Bacon Burger three weeks ago.
Why does the click-through rate on my website peak at 9 A.M.?
Data is used everywhere for everything in our lives.
In 2013, IBM published an astonishing figure: they estimated that approximately 2.5 quintillion bytes of data were being generated every day and that 90% of the world’s data had been generated in the previous two years. If you search for an update to these numbers in 2019, you will most likely find that people have simply added the word “over”. The scale of data generation is beyond measurement.
We are really good at generating data. As a consequence, data analytics is probably the most important skill a person can acquire, regardless of their core professional skills.
“Being able to look at various pieces of data and draw a conclusion is probably the most valuable skill for any employee to have, and surprisingly it’s something that’s too often missing from otherwise technically advanced employees.” — Venture Beat
There is no question about it: people with analytics skills are able to command higher salaries and enjoy a distinct advantage in the job market.
Data Analytics for Today’s Workforce
Most adults have little to no experience in data analytics. NCLab is pleased to offer a solution tailored for beginners. After completing this self-paced comprehensive curriculum, students will be ready to start using data analytics on the job, whether blending it into their existing work or starting a career as an entry-level analyst. For colleges, NCLab includes a student management system that provides real-time data to an instructor supervising the courses. The curriculum includes three courses:
- Intro to PostgreSQL for Data Science,
- Intro to Python for Data Analytics, and
- Intro to Predictive Analytics.
NCLab’s approach to online learning has been developed and perfected over the last 8 years. All courses are built on a carefully designed structure that results in an extremely smooth learning curve. Large concepts are broken down into simple steps and explained in detail.
The courses are hands-on. Students learn actively rather than simply viewing instructional videos. Tutorials, videos, and examples are combined with interactive exercises where students solve realistic tasks, progressing from simple to advanced as new skills are learned. Every task is instantly checked by the server and students are provided with feedback and help as needed. Years of use by institutions and individuals have demonstrated that this NCLab course structure results in an efficient learning experience for all learners.
PostgreSQL is a modern version of the Structured Query Language (SQL). SQL is used to communicate with database servers. The language consists of queries and conditions whose objective is to extract data of interest from a large database. SQL statements can be written for requests such as “Give me all business transactions which involve customer John Smith and which occurred between January 1, 2018 and June 30, 2018”, or “Calculate the average age of patients who meet a given medical condition”.
The NCLab PostgreSQL course begins with basic concepts and commands, not assuming any prior knowledge of data analytics, mathematics, or programming. While there are no formal prerequisites, the courses are primarily designed for postsecondary students.
The course opens with key concepts related to storing and analyzing data. It compares different types of database systems with a focus on the principles of RDBMS (relational database management systems) and explores the differences between the leading open source SQL flavors: MySQL, SQLite, and PostgreSQL.
The NCLab PostgreSQL course is the most comprehensive SQL course available online. It consists of 8 units and includes over 320 interactive levels and 40 quizzes. Students will:
Students also have access to a PostgreSQL app with numerous training databases where they can practice their skills, and personal file storage where they can store data and portfolio samples.
These SQL skills are invaluable, whether the student goes on to using one of many specialized data analytics apps, or write the SQL queries directly to a database.
Intro to Python for Data Science
While the PostgreSQL language makes it possible to communicate with a database server and extract data of interest, it was not designed to analyze and visualize the data. That’s where Python comes into play. Python is incredibly useful for this purpose and is easy to learn. Python currently is the most popular language for data analysis and visualization, and Python programming skills are in high demand by employers.
The Intro to Python for Data Science course assumes no prior experience in computer programming. However, complete beginners may find that they need to build computational thinking skills before programming in Python. NCLab’s flagship course, “Intro to Computational Thinking with Karel the Robot”, is recommended as a powerful visual pathway to developing computational skills. Karel has successfully trained students from middle school to college level.
The Intro to Python for Data Science course provides an intensive introduction to Python programming and to specific skills and libraries needed for Data Analytics. Examples from data science are used throughout the two-unit course.
Python can be used right away by non-programmers as a powerful command-line scientific calculator. The course begins by exploring these capabilities and progresses through variables, text string operations, functions, tuples, lists, sets, the for-loop, Boolean logic, conditional statements and expressions, the while-loop, file operations, and working with dictionaries.
The course further introduces fundamental concepts of Data Science, including Probability Density Functions (PDFs), Cumulative Distribution Functions (CDF), and essential numerical methods for solving nonlinear equations and optimization problems. Whether writing the code manually or calling it from a library, understanding these concepts will ensure that the analysis is done correctly.
Intro to Predictive Data Analytics
In this course, students put data to work, using Python and its powerful free libraries Pandas, Seaborn, Scipy, Numpy, Matplotlib, and Statsmodels. They learn to read, clean, analyze and visualize data effectively and painlessly. They are introduced to training and testing data sets, multiple linear regression, logistic regression, and quantitative analysis.
The one-unit course focuses on using Python libraries to solve practical applications rather than on the underlying math concepts. The libraries do the number-crunching behind the scenes. However, students learn enough statistical and analytical concepts and procedures in the tutorials to use these libraries effectively. This foundation is invaluable, whether they continue to use free Python libraries for analysis and visualization in their own work, or move on to a commercial analytics/visualization product specific to your industry.
NCLab is committed to educating our workforce for Industry 4.0. These three courses provide a solid introduction to data analytics, and more courses are in the pipeline. Please contact email@example.com if your organization would like to offer these courses to students or employees. As an individual, you can try the courses for free by following this link: https://nclab.com/learn-sql/.