Course Overview
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. This course includes hands on activities for each topic area.
Course Objectives
- 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.
Who Should Attend?
This course is designed for business professionals who leverage data to address business issues. The typical student in this course will have several years of experience with computing technology, including some aptitude in computer programming.
Course Prerequisites
What’s included?
- Authorized Courseware
- Intensive Hands on Skills Development with an Experienced Subject Matter Expert
- Hands-on practice on real Servers and extended lab support 1.800.482.3172
- Examination Vouchers & Onsite Certification Testing- (excluding Adobe and PMP Boot Camps)
- Academy Code of Honor: Test Pass Guarantee
- Optional: Package for Hotel Accommodations, Lunch and Transportation
With several convenient training delivery methods offered, The Academy makes getting the training you need easy. Whether you prefer to learn in a classroom or an online live learning virtual environment, training videos hosted online, and private group classes hosted at your site. We offer expert instruction to individuals, government agencies, non-profits, and corporations. Our live classes, on-sites, and online training videos all feature certified instructors who teach a detailed curriculum and share their expertise and insights with trainees. No matter how you prefer to receive the training, you can count on The Academy for an engaging and effective learning experience.
Methods
- Instructor-Led (the best training format we offer)
- Live Online Classroom – Online Instructor-Led
- Self-Paced Video
Speak to an Admissions Representative for complete details
| Start | Finish | Public Price | Public Enroll | Private Price | Private Enroll |
|---|---|---|---|---|---|
| 12/8/2025 | 12/12/2025 | ||||
| 12/29/2025 | 1/2/2026 | ||||
| 1/19/2026 | 1/23/2026 | ||||
| 2/9/2026 | 2/13/2026 | ||||
| 3/2/2026 | 3/6/2026 | ||||
| 3/23/2026 | 3/27/2026 | ||||
| 4/13/2026 | 4/17/2026 | ||||
| 5/4/2026 | 5/8/2026 | ||||
| 5/25/2026 | 5/29/2026 | ||||
| 6/15/2026 | 6/19/2026 | ||||
| 7/6/2026 | 7/10/2026 | ||||
| 7/27/2026 | 7/31/2026 | ||||
| 8/17/2026 | 8/21/2026 | ||||
| 9/7/2026 | 9/11/2026 | ||||
| 9/28/2026 | 10/2/2026 | ||||
| 10/19/2026 | 10/23/2026 | ||||
| 11/9/2026 | 11/13/2026 | ||||
| 11/30/2026 | 12/4/2026 | ||||
| 12/21/2026 | 12/25/2026 | ||||
| 1/11/2027 | 1/15/2027 |
Agenda
Duration
5 Days
1 – Addressing Business Issues with Data Science
- Topic A: Initiate a Data Science Project
- Topic B: Formulate a Data Science Problem
2 – Extracting, Transforming, and Loading Data
- Topic A: Extract Data
- Topic B: Transform Data
- Topic C: Load Data
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
4 – Designing a Machine Learning Approach
- Topic A: Identify Machine Learning Concepts
- Topic B: Test a Hypothesis
5 – Developing Classification Models
- Topic A: Train and Tune Classification Models
- Topic B: Evaluate Classification Models
6 – Developing Regression Models
- Topic A: Train and Tune Regression Models
- Topic B: Evaluate Regression Models
7 – Developing Clustering Models
- Topic A: Train and Tune Clustering Models
- Topic B: Evaluate Clustering Models
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
