Data Analytics Bootcamp

Unlock the power of data with our immersive Data Analytics Bootcamp – Empowering you to make informed decisions through cutting-edge analytics techniques.

100% Online | 24 Weeks



Course Enrollment


24 weeks


Online with Instructor-Led Training Sessions


$8,000, installment options available

Start Date

Begins every month. Please enroll now to select your start date.


Accelerate Your Data Analytics Career

The Data Analytics Bootcamp is a 24-week immersive dive into data and data architectures (databases, data warehouses, and data lakes), SQL, Python, data science, machine learning, and data loading, cleansing, and transformation. Students completing the bootcamp will possess skills to load, analyze, and visualize data. They will be well versed in SQL, the primary language for database operations and they will be able to use Python (the most widely-used programming language) to load, manipulate, and visualize data. They can also perform common machine-learning algorithms (clustering, classification, and predictive analysis). The bootcamp also introduces learners to Tableau--the most widely-used data mining and analysis tool.


Course Overview

Data analytics certifications provide students with a comprehensive understanding of data analytics principles and methods. With an in-depth knowledge of data analytics, students are able to understand and analyze data more effectively and efficiently. This knowledge can be used in the workplace to make better decisions, improve customer service, optimize processes, and develop new products and services. In addition, data analytics certifications provide students with the skills and knowledge needed to pursue advanced analytics and data science roles. Finally, the certification can open up the door to a variety of career opportunities, including data analyst, data scientist, and business intelligence analyst.


Designed For:

Data analytics is a relatively new and rapidly growing field, so the career prospects are excellent. Data analysts are in high demand, especially in the tech industry, and the field is expected to continue to grow. Data analysts can find jobs in various industries such as healthcare, finance, retail, and more. Those who specialize in data analytics can also find roles in data science, machine learning, and artificial intelligence. Data analytics skills are becoming more and more valuable, so those who complete a data analytics course can expect to find good job opportunities in their field. The salary of a data analytics programmer will vary depending on the job role and company, but generally, the salary range is between $60,000 and $120,000 per year. Additionally, many data analytics programmers may receive bonuses and other forms of compensation depending on their performance and the success of the projects they are working on. There are a wide range of data-related jobs:

  • Database administrator (DBA)
  • Data engineer
  • Data analyst
  • Data visualizer
  • Data scientist
  • Data architect
  • Data programmer

Skills Covered:

Upon completion of this credential, you will be able to:

  • Create and manipulate databases using SQL
  • Create Python scripts to load, cleanse, manipulate, and visualize data
  • Perform key machine-learning algorithms like clustering, classification, and predictive analysis using Python
  • Visualize data using a variety of tools
  • Perform extract, transform, and load operations applying data cleansing and quality operations
  • Analyze data using Tableau
  • Leverage and present data on the cloud


The Data Analytics course provides a comprehensive introduction to the field of data analytics, covering essential topics and skills that are necessary for success in the industry. The course is divided into nine modules, each of which focuses on a different aspect of data analytics, including databases, SQL, Python, data quality and cleansing, visualization, statistics, and machine learning. Students will learn how to manage and store data effectively, perform data analysis and manipulation using SQL and Python, ensure data quality and consistency, and create compelling visualizations and dashboards using tools like Tableau. The course also covers cloud-based tools and technologies, as well as machine learning algorithms, which are becoming increasingly important in the field. Overall, the Data Analytics course provides students with a strong foundation in the fundamental concepts and skills required for a successful career in data analytics.

Module 1: Databases, Data Lakes, and Data Warehouses

  • Understanding the differences between databases, data lakes, and data warehouses
  • Knowledge of different types of databases, including relational and NoSQL databases
  • Ability to design and implement a database schema

Module 2: SQL

  • Understanding of basic SQL concepts, including SELECT statements and table joins
  • Ability to use SQL to retrieve and manipulate data
  • Understanding of SQL functions and stored procedures

Module 3: Data Analytics and the Cloud

  • Understanding of cloud computing and its role in data analytics Knowledge of popular cloud platforms for data analytics, such as AWS and Google Cloud Platform
  • Ability to set up and manage a cloud-based data analytics environment

Module 4: Python

  • Understanding of basic Python concepts, such as data types and control flow statements
  • Ability to write Python scripts to perform data manipulation and analysis
  • Knowledge of popular Python libraries for data analytics, such as Pandas and Matplotlib

Module 5: Data Quality and Cleansing

  • Understanding of common data quality issues and methods for detecting and resolving them
  • Ability to use Python to clean and pre-process data
  • Knowledge of data profiling and data auditing techniques

Module 6: Visualizations

  • Understanding of the principles of effective data visualization Ability to create informative and visually appealing data visualizations using Tableau and Python
  • Knowledge of different types of visualizations and when to use them

Module 7: A Statistics Foundation

  • Understanding of basic statistical concepts, such as probability distributions and hypothesis testing
  • Ability to use statistical methods to analyze data and draw conclusions, knowledge of common statistical models used in data analytics, such as linear regression and logistic regression

Module 8: Planning and Scoping

  • Understanding of basic machine learning concepts, including supervised and unsupervised learning
  • Ability to use Python libraries, such as Scikit-learn and TensorFlow, to build machine learning models
  • Knowledge of common machine learning algorithms, such as k-means clustering and decision trees

Module 9: Tableau

  • Understanding of the Tableau interface and data visualization workflow
  • Ability to create interactive dashboards and visualizations in Tableau
  • Knowledge of advanced Tableau features, such as data blending and calculated fields business or working on a freelance basis

Subject Matter Expert



Dr. Kris Jamsa

Dr. Kris Jamsa wrote his first computer program in Algol, using punched cards, while attending the United States Air Force Academy. Since then, he has spent his career wrangling data and programs that use it. Jamsa has a Ph.D. in Computer Science, a second Ph.D. in Education and Masters’ Degrees in Computer Science, Information Security, Project Management, Education, and Business. He is the author of 119 books on all aspects of programming, computing, and data analytics.

Jamsa has strong knowledge of SQL, databases, data lakes, and data warehouses. He is a hands-on data scientist using Python and R. He has been a CTO, CIO, and Executive Vice President of Data Science.

Kris lives with his wife, Debbie, on their ranch in Prescott, Arizona. When he is not in front of a computer screen, you can find him spending time with their horses and dogs.



One Time Payment


For entire bootcamp

Paying the total cost of the bootcamp upfront.

Full access to the course

Financial Simplicity

Full support

Certificate of completion



Pay over the course of the bootcamp


per month for five months


Course Enrollment

Dividing the total cost into equal monthly payments.

Full access to the course

Payment flexibility

Full support

Certificate of completion


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