Advanced Business Analytics using Python x Power BI (APBI)
Enhance your Data Analytics prowess by combining Python with Power BI leveraging the strengths of both tools. Python, one of the most popular programming languages can be used for complex data analysis, statistical modeling, machine learning, and data preprocessing tasks. When used together with Power BI, a business analytics tool by Microsoft, it can create visually appealing and interactive dashboards and reports to effectively communicate the insights derived from Python analysis to stakeholders.
- Duration: 3 Days / 24 Hours
- Certification: Participants will receive a Certificate of Competency upon successfully completing the course and passing the examination
Select your preferred batch for more information
For corporate booking or course customization, Email Us or Speak to our Education Officer
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Pre-requisite
No pre-requisite. Suitable for everyone with and without prior technology experience.
Who Should Attend
Data Analysts, Business Analysts, Data Scientists, IT Professionals, Researchers, Consultants, Students and Aspiring Data Professionals, Key Decision Makers, Business Leaders, Business Process Outsourcing (BPO) Professionals, Anyone interested in acquiring knowledge and skills in Data Analytics
Key Features
- Technology-Based Training
- Open Source Tools
- 80% Hands-On Exercises / 20% Theory
- Designed by Industry Leaders and Subject-Matter Experts
- Progressive Learning
- Highly Interactive, Supportive and Encouraging
- Be Recognized as a Casugol Certified Professional
Course Objective
- Acquire the essential knowledge and technical skills on how data analytics can be used by organizations to enhance decision-making and uncover hidden data insights.
- Learn the core components of Data Analytics, Data Preprocessing and Cleaning, Data Mining, Data Warehousing, and Visualization using Power BI, and Python Programming
Examination
Participants are required to attempt an examination upon completion of course. This exam tests a candidate’s knowledge and skills related to Digital Transformation based on the syllabus covered
Participants are expected to score a minimum of 70% to pass the examination
Why Data Analytics using Python x Power BI (DPBI)?
- Combine the Power of Python Programming and Power BI for Data Analytics
- Global Recognition
- Networking Opportunities
- Career Advancement
- Job Opportunities in the Digital Economy
- Increase Earning Potential
- Derive Valuable Insights and Make Better Decisions with Data
Course Outline
Data Analytics using Python x Power BI (DPBI) involves immersive hands-on experiences, thorough utilization of real-world case studies, practical exercises, and collaborative group discussions.
Be Recognized as a CASUGOL Certified Professional
Add Value to your already prolific portfolio a Certificate of Competency from CASUGOL.
Awarded upon completing and meeting all requirements of the course.
All certificates issued by CASUGOL are to individuals who have successfully completed CASUGOL Certification Programs / Executive Workshops and have fulfilled all requirements by demonstrating proficiency in applying the knowledge and skills acquired.
Stories from Our Learners
Find out what it's like to take a CASUGOL Course from current and past learners.
Advance Your Business | Career to the Next Level
Face-to-Face and Online Zoom - Live options available. Select your preferred batch below.
For corporate booking or course customization, Email Us or Speak to our Education Officer
Click Here for More Info on Course
Course Features
- Lectures 59
- Quiz 0
- Duration 24 hours
- Skill level All levels
- Language English
- Students 0
- Assessments Self
- 8 Sections
- 59 Lessons
- 24 Hours
- Module 1 - Introduction to Data AnalyticsDelve into data types, sources, and analytics methodologies. Participants learn to collect, clean, analyze, and visualize data, utilizing tools like Python. In this topic, learners will acquire foundational knowledge for extracting insights and driving informed decisions across diverse fields.6
- Module 2 - Different Types of Analytics and ApplicationLearn how Descriptive, Diagnostic, Predictive, and Prescriptive analytics is being applied across industries for tasks like performance analysis, anomaly detection, forecasting, and decision optimization. Develop versatile skills crucial for addressing complex challenges and driving innovation through data-driven strategies.7
- Module 3 - Deep Dive into Python Programming for Data AnalyticsImmerses in Python's intricacies for data analysis. In this module, learners will have the opportunity to explore popular Python libraries like Pandas, NumPy, and Matplotlib. Acquire essential knowledge on data manipulation, visualization, and statistical analysis.10
- 3.0Introduction to Python Programming
- 3.1Setting up Python IDE and Programming Environment
- 3.2Understanding Structure of Python Programming
- 3.3Python Variables: Integer, Floats, Strings
- 3.4Using of List vs. Dictionary
- 3.5Operators and Loops: If-Else, For, While, Break, Continue
- 3.6Understanding Modules in Python
- 3.7Popular Python Libraries for Data Analytics (NumPy, Pandas, MatPlotLib, Seaborn)
- 3.8Data Pre-processing, Data Cleaning, and Data Engineering
- 3.9Data Visualization using Python Programming
- Module 4 - Data Mining Processes for Data AnalyticsUnderstanding the data analytics processes provide learners with a systematic way to extraction of valuable patterns and insights from vast datasets. In this module, Learners will explore key techniques like data preprocessing, pattern discovery, and predictive modeling.7
- Module 5 - Data Mining TechniquesFrom classification and clustering to association rule mining and anomaly detection, learners will acquire first-hand experience on the diverse approaches to Data Mining. This module equips Learners with the essential skills required to apply these techniques effectively, enabling informed decision-making and strategic planning across various domains.8
- Module 6 - Deep Dive into Visualization with PythonExplore intricate visualizations for effective data communication using popular Python visualization libraries like Matplotlib and Seaborn. Acquire skills required to create compelling visual narratives, enabling deeper insights and clearer understanding of complex datasets.7
- 6.0Data Visualization and Data Exploration
- 6.1Comparison Plots (Line Chart, Bar Chart, Radar Chart)
- 6.2Relation Plots (Scatter Plot, Bubble Plot, Correlogram, Heatmap)
- 6.3Composition Plots (Pie Chart, Stacked Bar Chart, Stacked Area Chart)
- 6.4Distribution Plots (Histogram, Density Plot, Box Plot, Violin Plot)
- 6.5Geo Plots (Dot Map, Choropleth Map, Connection Map)
- 6.6Enhancement of Visualization
- Module 7 - MatPlotLib and Seaborn Libraries in Python for VisualizationDevelop deep knowledge on how to create diverse plots, customize visualizations, and enhance data communication using MatPlotLib and Seaborn for visualization. Through extensive hands-on, Learners can produce insightful and visually appealing graphs, empowering effective analysis and presentation of complex datasets.6
- 7.0Deep Dive into Matplotlib in Python
- 7.1Essential Matplotlib Components for Plotting
- 7.2Basic Plots, Layouts, Images, and Mathematical Expressions using Matplotlib
- 7.3Introduction to Seaborn in Python
- 7.4Kernel Density Estimation, Bivariate Distribution, Pairwise Relationships
- 7.5Multi-plots, Regression Plots, Squarify, and Geospatial Plotting using Seaborn
- Module 8 - Enabling Python in Power BIIntegrates the analytical capabilities of Python with the visualization power of Power BI. Leverage Python scripts for data preparation, advanced analytics, and custom visualizations within Power BI reports and dashboards.8
- 8.0Setup Python integration within Power BI Desktop
- 8.1Using Python Scripts within Power Query for Data Transformation
- 8.2Integrating Python Visualizations into Power BI reports
- 8.3Python-based Machine Learning Models e.g. scikit-learn or TensorFlow, Power BI
- 8.4Passing parameters from Power BI to Python scripts
- 8.5Power BI Slicers and Filters with Python
- 8.6Performance Optimization of Power BI Report
- 8.7Real-time Data Analysis
Requirements
- No pre-requisite. Suitable for everyone with and without prior technology experience.
Features
- Technology-Based Training
- Open Source Tools
- 80% Hands-On Exercises / 20% Theory
- Designed by Industry Leaders and Subject-Matter Experts
- Progressive Learning
- Highly Interactive, Supportive and Encouraging
- Be Recognized as a Casugol Certified Professional
Target audiences
- IT Professionals
- CEO
- Directors
- CTOs
- CSOs
- CISOs
- CIOs
- Data Analysts
- Data Professionals
- Business Owners
- Data Management (Policy, Quality)
- Anyone interested in acquiring knowledge and skills in Data Governance
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