Basic Business Analytics: Insights for Competitive Advantage

"Business Analytics / Business Intelligence" is a course designed to provide students with an understanding of how organisations can use data and analytics to make informed decisions and drive business success. The course covers the basics of data collection and management, data visualisation, and statistical analysis. Topics such as predictive modelling, data mining, and machine learning are also covered to provide students with a comprehensive understanding of modern business analytics techniques. The course emphasises the use of practical tools and methods, including spreadsheets, statistical software, and dashboards, to analyse and interpret data. The goal of this course is to equip students with the skills and knowledge necessary to become proficient in business analytics and make data-driven decisions in a variety of business settings.

• Introduction to Business Analytics 03:00

  • 1: Introduction to Business Analytics Preview 03:00

• Data Collection and Preparation 06:00

  • 2: Data Collection and Preparation 06:00

• Exploratory Data Analysis (EDA) 06:00

  • 3: Exploratory Data Analysis (EDA) 06:00

• Introduction to Statistical Concepts 06:00

  • 4: Introduction to Statistical Concepts 06:00

• Data Visualization and Exploration 02:00

  • 5: Data Visualization and Exploration 02:00

• Regression Analysis 05:00

  • 6: Regression Analysis 05:00

• Predictive Modelling 03:00

  • 7: Predictive Modelling 03:00

• Time Series Analysis 05:00

  • 8: Time Series Analysis 05:00

• Clustering and Segmentation 05:00

  • 9: Clustering and Segmentation 05:00

• A/B Testing and Experimental Design 06:00

  • 10: A/B Testing and Experimental Design 06:00

• Data Mining 04:00

  • 11: Data Mining 04:00

• Machine Learning 04:00

  • 12: Machine Learning 04:00

• Business Intelligence and Dashboards 05:00

  • 13: Business Intelligence and Dashboards 05:00

Exciting Adventures Await: Discover the Fascinating Topics This Course Will Explore!

Subjects to be addressed within this course:

Chapter 1: Introduction to Business Analytics

1. Definition and Purpose of Business Analytics
2. Overview of Data-Driven Decision Making
3. Importance of Data Management and Preparation

Chapter 2: Data Collection and Preparation

1. Data sources and types (structured vs. unstructured data)
2. Data collection methods and tools
3. Data cleaning, preprocessing, and data quality assurance

Chapter 3: Exploratory Data Analysis (EDA)

1. Descriptive statistics and data visualisation techniques
2. Identifying patterns, outliers, and trends in data
3. EDA best practices and common pitfalls

Chapter 4: Introduction to Statistical Concepts

1. Probability and probability distributions
2. Sampling and sampling distributions
3. Hypothesis testing and confidence intervals

Chapter 5: Data Visualization and Exploration

1. Introduction to Data Visualization Techniques
2. Creating Effective Charts and Graphs
3. Exploring Data Patterns and Trends

Chapter 6: Regression Analysis

1. Simple linear regression
2. Multiple linear regression
3. Model evaluation and interpretation

Chapter 7: Predictive Modelling

1. Overview of Predictive Modeling Techniques
2. Simple Linear and Logistic Regression
3. Model Selection and Evaluation
4. Non-Linear Regression

Chapter 8: Time Series Analysis

1. Understanding time series data
2. Forecasting methods (e.g., moving averages, exponential smoothing)
3. Seasonality and trend analysis

Chapter 9: Clustering and Segmentation

1. K-means clustering
2. Hierarchical clustering
3. Applications in customer segmentation and market analysis

Chapter 10: A/B Testing and Experimental Design

1. Designing experiments for business decisions
2. Hypothesis testing in A/B testing
3. Interpreting and acting on experimental results

Chapter 11: Data Mining

1. Overview of Data Mining Techniques
2. Clustering and Association Rules
3. Decision Trees and Random Forests
4. Text Mining and Sentiment Analysis

Chapter 12: Machine Learning

1. Overview of Machine Learning Algorithms
2. Supervised and Unsupervised Learning
3. Neural Networks and Deep Learning
4. Natural Language Processing

Chapter 13: Business Intelligence and Dashboards

1. Overview of Business Intelligence Tools and Dashboards
2. Designing Effective Dashboards
3. Integrating Data from Multiple Sources
4. Creating Interactive Reports and Visualisations

Unlock Your Potential: Enroll Today and Receive a Complimentary Digital Certificate Upon Course Completion!

The course "Basic Business Analytics: Insights for Competitive Advantage" is designed for individuals seeking to gain a fundamental understanding of data-driven decision-making in the business world. It is ideal for early-career professionals, recent graduates, entrepreneurs, and anyone interested in harnessing the power of data to drive strategic decisions and gain a competitive edge.

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Reed Courses Certificate of Completion

Digital certificate - Included