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Digital Transformation: Advanced Data Science Course (3 Modules)

The Digital Transformation: Advanced Data Science course is comprised of three modules that delve into the practical application of contemporary data science techniques and algorithms involving Artificial Intelligence (AI), Machine Learning and Big Data Analytics.

Each module has a set of lessons and is further supplemented with exercises and practice questions to help reinforce your understanding of key topics. Completing this course also prepares you for the official certification exam, as explained on the Digital Transformation Data Scientist Certification page.

Further resources are available to assist you with the completion of this course and preparation for the certification exam. These include downloadable digital course PDFs, printed course materials that can be shipped to your location, as well as coaching and instructor-led training services available by Arcitura and its training partner network. You can purchase coaching time on an hourly basis and instructor-led training workshops are available for individuals and groups.

This course is available via two separate eLearning platforms, each of which has different features and benefits. Upon clicking the Enroll button, you will be able to choose the eLearning option that works best for you.

Contact [email protected] with any questions.

Program: Digital Transformation Professional Academy

Prerequisites: Digital Transformation: Fundamental Data Science

Duration: 30 hours

Price: from $29

Corresponding Certification:
Digital Transformation Data Scientist


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Workbook Lessons


Video Lessons


Reference Posters


Interactive Exercises


Graded Self-Test


Completion Certificate


Course Modules

MODULE 12 | Advanced Big Data Analysis & Analytics
Provides an in-depth overview of essential and advanced topic areas pertaining to data science and analysis techniques relevant and unique to Big Data with an emphasis on how analysis and analytics need to be carried out individually and collectively in support of the distinct characteristics, requirements and challenges associated with Big Data datasets.

MODULE 13 | Advanced Machine Learning
Delves into the many algorithms, methods and models of contemporary Machine Learning practices to explore how a range of different business problems can be solved by utilizing and combining proven Machine Learning techniques.

MODULE 14 | Advanced AI
Covers a series of practices for preparing and working with data for training and running contemporary AI systems and neural networks. It further provides techniques for designing and optimizing neural networks, including approaches for measuring and tuning neural network model performance.