
Get started with Python for business analytics by setting up a Python environment, virtual environments, and essential libraries, and explore R for data analysis, visualization, and statistical modeling.
Master data cleaning, preprocessing, exploratory data analysis, predictive modeling, reporting, dashboards, and optimization using imputation, normalization, one hot encoding, and visualizations to derive actionable business insights.
Explore regression analysis and build a linear regression model in R and Python, using a two-column data frame to estimate intercept, slope, and R-squared.
Explore Python basics with variables and data types, including integers, floats, strings, and booleans, and learn how dynamic typing and the print function reveal values.
Explore business analytics with Python, using pandas, numpy, matplotlib, seaborn, scikit-learn, statsmodels, and SQL alchemy to collect, clean, visualize, and model data for insights.
Explore sales analytics with interactive Plotly visualizations and dash dashboards, clean data, perform eda, and build a random forest model evaluated by mean absolute error.
Understand regression analysis to model the relationship between variables and predict outcomes with linear regression, using Python with pandas and statsmodels to fit an OLS model and inspect the summary.
Apply statistics to business decision making through data collection, analysis, and hypothesis testing. Use regression and time series forecasting to inform pricing, marketing, and operations.
The lecture demonstrates descriptive statistics with Python, using pandas to load data and compute mean, median, and standard deviation, and performs a one-sample t-test against a population mean of 500.
Learn to perform regression analysis with python statsmodels, prepare data with an intercept, fit an ols model, and interpret p-values and r-squared to decide on marketing spend.
Plan and monitor business analytics activities by outlining tasks, estimating effort, developing a schedule, and assigning responsibilities to ensure stakeholder requirements are met and value is delivered.
Plan how to inform stakeholders and team members through emails, meetings, and reports. Identify communication needs, select methods, and develop a schedule to ensure timely updates.
Explore strategic planning tools and techniques, including swot and pest analyses, porter's five forces, balanced scorecard, risk assessment, fmea, scenario planning, and collaboration tools for business analytics.
Explore how business intelligence transforms raw data into actionable insights for strategic and tactical decisions through data collection, integration, storage, analysis, and visualization.
Define project objectives, collect and clean data, explore and analyze, visualize results, interpret findings, and implement monitoring to turn raw data into actionable insight.
Interpret results by extracting insights from data visualizations and statistics to draw conclusions aligned with business objectives, highlighting key patterns, diminishing returns, and implications for marketing spend and sales.
Explore essential data science learning resources for business, including books, online courses, and certifications, and master a practical data analytics process from data collection to decision making.
Description
Take the next step in your career! Whether you’re an up-and-coming business analyst, an experienced business dashboard designer, an aspiring business manager, or a budding business visualization expert, this course is an opportunity to sharpen your business analysis skills, increase your effectiveness in business dashboard design, performance metrics, and user development, and make a positive and lasting impact in your organization.
With this course as your guide, you learn how to:
● All the fundamental functions and skills required for effective business analysis practice.
● Transform Goals, Overview, Definition, and Categories of Business Analysis, Stakeholders Interested in Business Analysis, and Goals of Business Analysis.
● Get access to recommended templates and formats for detailed business analysis and business dashboard reporting.
● Explore business analysis assessments, understanding various business analysis techniques, and how to present findings effectively with useful templates and frameworks.
● Invest in yourself today by enhancing your skills in business analysis, and reap the benefits for years to come.
The Frameworks of the Course
● Engaging video tutorials, case studies, analyses, downloadable resources, and interactive exercises. This course is designed to cover the Goals, Overview, Definition, and Categories of business analysis, the roles and responsibilities of key stakeholders in business dashboard design, and foundational concepts in business data preparation, performance metrics, and user engagement.
● The core concepts of business visualization, including understanding business data preparation (dashboard requirements), the performance metrics process, the presentation of business dashboard roles and responsibilities, user engagement strategies, and methods for assessing business dashboard effectiveness. Preparing and implementing strategies for performance metrics and user development, including techniques for evaluating and enhancing dashboard roles and organizational effectiveness.
● The course includes multiple case studies, resources such as templates, formats, worksheets, reading materials, quizzes, self-assessments, and assignments to enhance and deepen your understanding of key business analysis concepts, including business data preparation, performance metrics, user engagement, and business dashboard behavior.
In the first part of the course, you’ll learn the details of the Goals, Overview, Definition, and Categories of business analysis, the roles and responsibilities of key stakeholders in business dashboard design, and foundational principles in business data preparation, performance metrics, and user engagement. Part 1 covers the basics of designing effective business dashboard elements, enhancing user performance, and implementing performance metrics systems.
In the middle part of the course, you’ll develop knowledge of business data preparation and business dashboard design, understanding various roles and responsibilities within a business dashboard, user performance metrics, methods for assessing business dashboard effectiveness and user engagement, and techniques for implementing effective performance metrics systems. You’ll also explore practical strategies for enhancing business dashboard effectiveness and user development.
In the final part of the course, you’ll develop knowledge in implementing advanced business visualization practices, including designing effective performance metrics systems, developing strategies for user engagement and business dashboard development, and understanding the limitations of performance metrics techniques. You will receive full support, and all your queries will be answered within 48 hours.
Course Content:
Part 1
Introduction and Study Plan
● Introduction and know your Instructor
● Study Plan and Structure of the Course
1. Introduction to Programming Language
● Introduction to Programming Language
● Common Application
● Data Cleaning
● Getting Started
● Key Packages and Tools
● Building a Predictive Model
● Key Concepts
● Steps in Statistical Analysis
● Regression Analysis
● Visualizing Data
● Getting Started
2. Basic Syntax and Data Types
● Basic Syntax and Data Types
● List, Tuples and Dictionaries
● Module and Libraries
● Matplotlib
● Business Analytics with Python
3. Data Visualization With Python and Tableau
● Data Visualization With Python and Tableau
● Seaborn
● Data Visualization With Tableau
● Integrating Python with Tableau
4. Analytics Foundation Using statistical Methods
● Analytics Foundation Using statistical Methods
● Hypothesis Testing
● Logistics Regression
5. Business Decision making using statistics
● Business Decision making using statistics
● Exam Workflow
● Descriptive Statistical Example
● Regression Analysis Example
● Business Analysis Planning and Monitoring
● Planning Business Analysis Communication
6. Strategy Analysis
● Strategy Analysis
● Developing a Change Strategy
● Tools and Techniques
7. Business Intelligence
● Business Intelligence
● BI tools and Technologies
8. Business Process
● Business Process
● Process Design
● Process Automation
● Process Monitoring and control
9. Excel and Advanced Excel
● Excel and Advanced Excel
● Example Conditional Formatting
● Example Power Query
10. Project
● Project
● Data Exploration and Analysis
● Data Visualization
● Interpret Results
● Communicate Findings
● Implement and Monitor
● Learning Resources
Part 2
1.Assignment: Data Collection and Management
2.Project:Enhancing Data Collection and Management for Improved Business Analytics
3.Assignment: Predictive Analytics
4.Project: Implementing Predictive Analytics to Optimize Customer Churn Prediction