What will you learn in this Advanced Business Analytics Specialization Course
Extract and manipulate data using SQL for business analysis.
Apply statistical methods for descriptive, predictive, and prescriptive analytics.
Develop optimization models to support decision-making processes.
Effectively communicate analytical findings to stakeholders.
Program Overview
1. Introduction to Data Analytics for Business
⏳ 11 hours
Learn the fundamentals of data analytics, including data management, SQL querying, and the data lifecycle.
2. Predictive Modeling and Analytics
⏳ 10 hours
Delve into predictive analytics techniques, exploring regression models, data visualization, and simulation methods.
3. Business Analytics for Decision Making
⏳ 8 hours
Understand optimization methods and their application in solving complex business problems.
4. Communicating Business Analytics Results
⏳ 7 hours
Develop skills to present analytical results effectively, focusing on data visualization and storytelling.
5. Advanced Business Analytics Capstone
⏳ 19 hours
Apply the knowledge gained to a real-world project, involving data analysis, model development, and presentation of insights.
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Job Outlook
Prepares learners for roles such as Business Analyst, Data Analyst, and Operations Analyst.
Applicable across various industries, including finance, marketing, and supply chain management.
Enhances employability by providing practical skills in data-driven decision-making.
Supports career advancement in fields requiring analytical and strategic thinking.
Explore More Learning Paths
Advance your expertise in data-driven decision-making and gain deeper insights into business performance. These related programs will help you strengthen your analytical mindset and master advanced tools for strategic growth.
Related Courses
Strategic Business Analytics Specialization Course — Learn how to translate complex data into actionable strategies that drive competitive advantage.
Business Analytics with Excel: Elementary to Advanced Course — Master Excel-based analytical techniques for data visualization, forecasting, and decision modeling.
Business Analytics Specialization Course — Build a solid foundation in business analytics, covering key concepts in statistics, data interpretation, and data-driven business problem solving.
Related Reading
How to become Business Analytics? — Explore how analytics empowers organizations to make smarter decisions and uncover hidden business opportunities.
Specification: Advanced Business Analytics Specialization Course
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FAQs
- Basic Excel skills are required.
- Familiarity with programming concepts is recommended.
- No prior advanced analytics experience is necessary.
- Beginners may need extra practice for statistical and optimization modules.
- Prior exposure accelerates understanding of hands-on projects.
- Capstone involves a real-world data analysis project.
- Projects cover SQL, predictive modeling, and optimization.
- Emphasizes translating insights into actionable business decisions.
- Builds portfolio-ready work for job applications.
- Simulates decision-making scenarios across multiple industries.
- Prepares for roles like Business Analyst, Data Analyst, and Operations Analyst.
- Teaches data extraction, manipulation, and communication to stakeholders.
- Builds skills applicable in finance, marketing, and supply chain management.
- Enhances employability by combining theoretical and practical knowledge.
- Supports career advancement in analytics-focused positions.
- Self-paced with lifetime access allows flexible scheduling.
- Each module ranges from 7–19 hours, manageable in short sessions.
- Hands-on exercises and projects can be completed incrementally.
- Supports learners balancing full-time work with professional development.
- Enables revisiting content for reinforcement as needed.
- Covers statistical, predictive, and optimization methods at an intermediate level.
- Some advanced topics may require additional study.
- Hands-on projects help reinforce theoretical concepts.
- Prior knowledge in Excel or basic statistics improves comprehension.
- Encourages learners to build quantitative skills alongside analytics practice.
