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%):
Practical Session (15%):
Group Project (25%):
Individual Assignment (20%):
Final Capstone Project and Certification Exam (25%):
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:
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].
VII. Contact Information
A. Instructor:
[Your Name]
[Your Email]
B. Company Information:
[Your Company Name]
[Your Company Email]
[Your Company Address]
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