Spezialisierung für AI-Enhanced Data Analysis: From Raw Data to Deep Insights

Description: This course delves into the world of data analysis with Python. You'll learn how to use libraries like pandas and Matplotlib to manipulate, analyze, and visualize data, extracting valuable insights and communicating findings effectively.

Benefits: Become proficient in data analysis techniques, enabling you to extract meaningful insights from data and present them in compelling visualizations. By the end of this course, you'll be able to: • Perform data cleaning, transformation, and manipulation using pandas. • Create various types of visualizations using Matplotlib. • Understand the fundamentals of generative AI and its applications in data analysis. • Implement basic machine learning models for data analysis. Tools/Software: Python, Jupyter Notebook, pandas, Matplotlib, Scikit-learn This course is for entry-Level professionals looking to build a foundational understanding and experience with Python, while seeking employment as a Python developer. No prior work experience or degree is required.

This course provides in-depth knowledge of analytical techniques and effective data visualization using Power BI. By the end of this course, you will be able to:

- Explain different analysis methods (correlation, time series, cluster, etc.) and their appropriate use. - Analyze data through visualizations in Power BI using different analysis methodologies - Leverage AI to explore data and gain insights. Here is a breakdown of what you'll cover: You will begin with statistical analysis fundamentals, master correlation, and exploratory data analysis, and understand business problems. As the course progresses, you will explore advanced topics like cluster analysis, cohort analysis, and geospatial data visualization. Additionally, you will learn about business intelligence concepts, including building time intelligence functions, conducting time series analysis, and leveraging AI-driven tools like key influencers and decomposition trees. With a strong emphasis on practical application, the course culminates in a hands-on final project, allowing you to synthesize your skills in a real-world scenario, making data-driven decision-making clear and impactful. This program is for anyone interested in data analytics and visualization; there are no prerequisites. To get the most out of the learning experience, it is recommended to follow the courses in sequence, as each one builds on the skills and knowledge gained in the previous ones. Before starting this course, you should be proficient in building data models, maintaining relationships in Power BI, and writing DAX expressions to enhance analysis. You should also understand the ethical implications of handling data. This knowledge will be essential as you learn advanced data analysis techniques and explore data through Power BI's visualizations, supported by AI-driven insights.