CNX011 - Certified Data Science Practitioner

Course Description

Bootcamp | 30 hours | 3.0 CEUs | $3,995

For a business to thrive in our data-driven world, it must treat data as one of its most important assets. Data is crucial for understanding where the business is and where it's headed. Not only can data reveal insights, it can also inform—by guiding decisions and influencing day-to-day operations. This calls for a robust workforce of professionals who can analyze, understand, manipulate, and present data within an effective and repeatable process framework. In other words, the business world needs data science practitioners. This course will enable you to bring value to the business by putting data science concepts into practice.

Not only does this class teach valuable practical Data Science skills but it also prepares you for the Certified Data Practitioner (CDSP), one attempt at the exam is included.  The Certified Data Science Practitioner™ (CDSP) is an industry-validated certification which helps professionals differentiate themselves by demonstrating their ability to put data science concepts into practice. Data can reveal insights and inform—by guiding decisions and influencing day-to-day operations. This calls for a robust workforce of professionals who can analyze, understand, manipulate, and present data within an effective and repeatable process framework. This certification validates candidates’ ability to use data science principles to address business issues, use multiple techniques to prepare and analyze data, evaluate datasets to extract valuable insights, and design a machine learning approach. In addition, it will validate skills to design, finalize, present, implement, and monitor a model to address issues regardless of business sector.

Course Outline

• Lesson 1: Addressing Business Issues with Data Science
  • Topic A: Initiate a Data Science Project
  • Topic B: Formulate a Data Science Problem
• Lesson 2: Extracting, Transforming, and Loading Data
  • Topic A: Extract Data
  • Topic B: Transform Data Topic C: Load Data
• Lesson 3: Analyzing Data
  • Topic A: Examine Data
  • Topic B: Explore the Underlying Distribution of Data
  • Topic C: Use Visualizations to Analyze Data
  • Topic D: Preprocess Data
• Lesson 4: Designing a Machine Learning Approach
  • Topic A: Identify Machine Learning Concepts
  • Topic B: Test a Hypothesis
• Lesson 5: Developing Classification Models
  • Topic A: Train and Tune Classification Models
  • Topic B: Evaluate Classification Models
• Lesson 6: Developing Regression Models
  • Topic A: Train and Tune Regression Models
  • Topic B: Evaluate Regression Models
• Lesson 7: Developing Clustering Models
  • Topic A: Train and Tune Clustering Models
  • Topic B: Evaluate Clustering Models
• Lesson 8: Finalizing a Data Science Project
  • Topic A: Communicate Results to Stakeholders
  • Topic B: Demonstrate Models in a Web App
  • Topic C: Implement and Test Production Pipelines

Learner Outcomes

In this course, you will implement data science techniques in order to achieve organizational goals. You will: 

• Use data science principles to address business issues
• Apply the extract, transform, and load (ETL) process to prepare datasets
• Use multiple techniques to analyze data and extract valuable insights
• Design a machine learning approach to address business issues
• Train, tune, and evaluate classification models
• Train, tune, and evaluate regression and forecasting models
• Train, tune, and evaluate clustering models
• Finalize a data science project by presenting models to an audience, putting models into production, and monitoring model performance

Additional Information

SLU's Course Kit: (included in the course fee):

• Authorized Digital Courseware
• Online labs
• One exam attempt

Duration