WSQ Python for Data Science (SF) (Synchronous and Asynchronous E-Learning)
About This Course
Learners in the "Python for Data Science" module will acquire fundamental knowledge and skills in Python programming, encompassing functions, conditional statements, and data processing. They will also gain insights into the business value of Power Platform, exploring its core components and dynamic decision-making within Power Automate workflows.
Through projects, learners will develop practical competencies. They will automate workflows using Power Automate Templates, enhancing efficiency and productivity. Additionally, learners will demonstrate their ability to implement dynamic decision-making through conditional branches, facilitating adaptable workflow structures. Another project involves automated document generation and tracking of approval status, showcasing proficiency in streamlining processes and maintaining transparency.
Furthermore, learners will apply their acquired skills to implement a data model and build a model-driven approach, contributing to effective data management and analysis. Lastly, they will construct a Canvas app, demonstrating proficiency in creating user-friendly interfaces for data visualization and interaction. Overall, this module equips learners with essential Python skills and practical experience in leveraging Power Platform for data-driven decision-making and process automation
What You'll Learn
Duration of the course is 80.5
Instructional Unit of this course is
1. Introduction to Python programming.
2. Functions, Conditional Statements, and Data Processing.
3. Business value of Power Platform
4. Exploring Power Automate Core Components
5. Dynamic Decision-Making in Power Automate Workflows.
Knowledge Outcomes:
Python Programming Fundamentals: Understanding of functions, conditional statements, and data processing in Python.
Power Platform Business Value: Insights into Power Platform’s role in enhancing business efficiency through automation.
Data Management Principles: Knowledge on implementing data models for effective data analysis.
Skills Outcomes:
Python Data Science Proficiency: Ability to perform data analysis and manipulation using Python.
Workflow Automation Skills: Skills in automating workflows and decision-making processes with Power Automate.
App Development Competency: Capability to develop data-driven applications using Power Platform, including model-driven and Canvas apps.
Entry Requirements
Academic Qualification: Minimum 1 credit in O Level or its equivalent
Experience: Minimum 1-year experience in any business process