Accredited Course

I. Accredited Course Information

Course Title	Certified Data Analytics Program
Instructor	[Your Name] [Your Email] Office Hours: Tuesdays & Thursdays, 3:00 PM - 5:00 PM
Course Code	CDA-3050
Course Description	This accredited course offers a comprehensive understanding of data analytics, covering data collection, processing, visualization, and interpretation. Participants will gain hands-on experience with industry-standard tools and techniques, equipping them with the skills needed to excel in the rapidly growing field of data analytics. The course includes case studies, practical exercises, and a capstone project to demonstrate mastery of the content.
Prerequisites	Basic knowledge of statistics and familiarity with Microsoft Excel or equivalent tools.
Duration	8 Weeks (16 Sessions)
Accreditation	Accredited by the Global Data Analytics Association (GDAA)

II. Learning Objectives

By the end of this accredited course, participants will be able to:

Collect and process large datasets using advanced tools and techniques.
Analyze and interpret data to make informed business decisions.
Visualize data effectively using industry-standard software.
Apply statistical methods to identify trends and patterns in data.
Develop and present data-driven insights through a comprehensive capstone project.

III. Course Schedule

Week	Topics Covered	Readings	Assignments/Activities
1-2	Introduction to Data Analytics Overview of data analytics Tools and software for data analysis Data collection techniques	Chapter 1 & 2 from "The Data Analyst's Toolkit" by Maria Gomez	Assignment 1: "Data Collection and Processing: Hands-on Exercise with Real-world Datasets"
3-4	Data Processing and Cleaning Handling missing data Data normalization and transformation Data cleaning best practices	Chapter 3 from "Data Wrangling with Python" by David Liu	Practical Session: "Data Cleaning Workshop: Preparing Data for Analysis"
5-6	Data Visualization Principles of effective data visualization Using visualization tools (e.g., Tableau, Power BI) Creating dashboards	Chapter 4 & 5 from "Visualizing Data" by Naomi Thompson	Group Project: "Designing and Presenting Interactive Dashboards for Business Insights"
7	Statistical Analysis Descriptive and inferential statistics Hypothesis testing and confidence intervals Regression analysis	Chapter 6 from "Statistics for Data Analysts" by Robert Parker	Individual Assignment: "Applying Statistical Methods to Analyze Business Trends"
8	Capstone Project and Certification Project work Presentation of findings Final certification assessment	Chapter 7 from "Capstone Success" by Elaine White	Final Capstone Project: "End-to-End Data Analysis Project: From Collection to Insight Presentation and Certification Exam"

IV. Assessment Methods

Participants will be assessed based on the following:

Assignment 1 (15%):
- Data collection and processing exercise involving real-world datasets.
Practical Session (15%):
- Hands-on workshop focusing on data cleaning techniques and best practices.
Group Project (25%):
- Collaborative design and presentation of interactive data dashboards.
Individual Assignment (20%):
- Application of statistical methods to analyze and interpret business trends.
Final Capstone Project and Certification Exam (25%):
- Comprehensive end-to-end data analysis project, followed by a certification exam to validate participants' knowledge and skills.

V. Required Texts and Resources

A. Textbooks:

"The Leadership Handbook" by Laura Green
ISBN: 978-1-234-56789-5
"Strategic Leadership" by James Roberts
ISBN: 978-1-234-56789-6
"Managing Conflict in Teams" by Sarah Brown
ISBN: 978-1-234-56789-7
"Leadership in Practice" by Emily Turner
ISBN: 978-1-234-56789-8
"Capstone Success" by Elaine White
ISBN: 978-1-234-56789-9

B. Online Resources:

[Your Company Website]
Data Analytics Hub
Global Data Analytics Association (GDAA)

VI. Course Policies

A. Attendance:

Regular attendance and participation are mandatory for successful course completion. Participants are expected to engage actively in all sessions and complete all assigned work.

B. Assignments:

All assignments must be submitted on time. Late submissions will incur a penalty unless an extension is granted by the instructor in advance.

C. Group Work:

Collaboration is a key component of this course. Participants are expected to work together effectively in groups and contribute equally to group projects.

D. Professional Conduct:

Participants must maintain a professional demeanor and adhere to ethical standards throughout the course. Respect for peers and instructors is essential.

E. Communication:

For any questions or concerns, participants should contact [Your Name] via [Your Email]. Course announcements and updates will be posted on [Your Company Website].