Description
The Exploratory Data Analysis (EDA) with Python course offers a hands-on approach to learning the fundamental techniques of exploring, cleaning, and understanding data using Python. EDA is a critical step in the data science process that helps uncover patterns, detect anomalies, test hypotheses, and check assumptions with the help of summary statistics and graphical representations. This course walks learners through practical, real-world examples using popular Python libraries like pandas, NumPy, Matplotlib, and Seaborn to perform EDA on datasets. By the end of the course, learners will have a solid foundation to analyse and draw insights from data independently, making them more efficient and effective in their data science roles.
Certification
Upon successful completion of the course, learners will receive a Certificate of Completion. This certification recognizes their proficiency in conducting Exploratory Data Analysis using Python and serves as evidence of their skills in data preparation, summarization, visualization, and handling outliers. The certification can be used to enhance professional profiles and resumes, demonstrating their ability to apply EDA techniques in various data-driven roles.
Audience:
This course is designed for:
- Aspiring Data Scientists who want to develop foundational skills in data exploration and analysis.
- Data Analysts seeking to improve their ability to clean, summarize, and visualize data using Python.
- Business Analysts looking to enhance their data analysis skills and provide insights for data-driven decision-making.
- Students and Researchers interested in learning how to efficiently explore and analyse datasets for their projects.
- Professionals transitioning to Data Science from other fields who wish to build hands-on Python experience in data exploration.
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