Data Science For Business Professionals

Übersicht

In today’s fast-paced digital economy, data is at the heart of every decision, making Data Science one of the most in-demand fields. Whether you are looking to enter the field of Data Science , improve your business analysis skills, or apply Machine Learning techniques to solve business challenges, this course will provide you with the essential knowledge to excel.

Lehrplan

• Introduction to Data Science
Overview of Data Science and its importance in business
Key roles and skills in Data Science
• Data Collection and Management
Types of data: structured vs. unstructured
Data collection techniques and sources
Data cleaning and preprocessing
• Exploratory Data Analysis (EDA)
Descriptive statistics
Data visualization techniques
Identifying patterns and outliers in data
• Introduction to Machine Learning
Supervised vs. unsupervised learning
Common algorithms: linear regression, decision trees, clustering
Evaluation and validation of models
• Applying Machine Learning to Business
Case studies of Machine Learning in business contexts
Solving business challenges with predictive models
Model deployment and maintenance
• Business Analytics
Key performance indicators and metrics
Dashboard creation and data storytelling
Scenario analysis and decision-making support
• Data-Driven Decision Making
Creating data-driven business strategies
Communicating data insights to stakeholders
Ethical considerations in data usage
• Tools and Technologies in Data Science
Overview of popular data science tools: Python, R, SQL
Introduction to software platforms for business analytics (e.g., Tableau, Power BI)
• Capstone Project
Real-world business data set analysis
Problem-solving using data science techniques
Presentation and interpretation of results to a business audience

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Fachgebiete

Data Science