#DATA ANALYSIS PROGRAMS ENGINEER HOW TO#
#DATA ANALYSIS PROGRAMS ENGINEER CODE#
#DATA ANALYSIS PROGRAMS ENGINEER PROFESSIONAL#

Instructional material equivalent to a one semester credit hour class.

The online delivery of each course is comprised of:

Students select their own pace towards completion of the Certification.

The option to take standalone courses for targeted learning or complete four courses to earn the certification.

Courses that focus on the most important components of data analytics.

Being taught by top faculty from The Ohio State University College of Engineering and Department of Statistics.

All courses are delivered in 100% distance learning format and asynchronously.

As a student in the program, you’ll enjoy:

#DATA ANALYSIS PROGRAMS ENGINEER PROFESSIONAL#

This combination enables students to build a portfolio of projects that demonstrate their newly acquired data skills to advance with their existing employer or stand out when applying for new opportunities.Īdvantages of this Data Analytics programīusy professionals find this program meets their professional goals while providing a flexible learning experience. Throughout the data analytics courses, students will use applied learning and work with real-world data sets.

Use Tableau, a high-fidelity tool to create data-driven visualizations.

Perform a Work Domain Analysis to reveal informative data relationships.

Use Python and TensorFlow to build flexible and efficient deep machine learning models.

Be able to construct, train, and apply deep neural networks and identify which deep learning methods are best suited for a given task.

#DATA ANALYSIS PROGRAMS ENGINEER HOW TO#

Be familiar with current machine learning models for different data types and how to evaluate and tune the performance of machine learning models.

#DATA ANALYSIS PROGRAMS ENGINEER CODE#

Be competent using a Python integrated development environment (IDE) to write well-structured code and Python libraries and toolkits to import/export and analyze data for machine learning.Apply the use of chatbot technology with text analytics using available cloud technology.Use different data mining modeling techniques and algorithms including decision trees, random forests, regression models, machine learning algorithms and how to apply them within common predictive models, and text analytics within classification models.

Learn the Cross-Industry Standard Process for Data Mining (CRISP-DM) methodology for projects including data preparation techniques, modeling, evaluating results, and how data can solve business problems.

Interpret linear association and conduct simple linear regression data analysis.Describe data graphically and numerically using statistical software.

The Certification in Practice of Data Analytics is designed to teach you to: The CPDA program currently includes six, non-credit courses and at least four must be successfully completed in order to earn the certificate of completion. While this program is offered through the College of Engineering, it is designed for people in any profession or industry and requires minimal knowledge about data analytics. Learn to ask the right questions, make inferences, and publish results. In addition, you will be able to apply what you're learning immediately to real-world situations. The Certification in Practice of Data Analytics (CPDA) offers working professionals the opportunity to acquire the knowledge and skills that support the management and use of big data. Data Analytics is a burgeoning field due to the exponential growth of information created with today’s sophisticated technologies.

Data analysis programs engineer