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Data Project Fundamentals: Skills and Techniques for Success

Learn data projects from start to finish! Master data profiling, modeling, testing & more. Hands-on skills for data analysis success.

4.7(23)
197students
5h 16m
Certificate
Jeremy Fletcher
Jeremy FletcherData Solution Expert

Course Content

Data Project Fundamentals: Skills and Techniques for Success is an all-levels Udemy course taught by Jeremy Fletcher. It runs 5h 16m, is taught in English, and includes a certificate of completion. Learners rate it 4.7 out of 5 from 23 reviews, with 197 students enrolled. It is a paid course, last updated December 2023.

Become a more rounded data professional with this comprehensive course! Learn the essential skills to excel throughout the entire data project lifecycle. We'll explore the techniques, challenges, and best practices at each stage, from initial data profiling to final data solution design.

This course covers a wide range of crucial topics including:

  • Data Profiling: Understand your data's characteristics and identify potential issues.
  • Data Mapping & Transformation: Learn how to clean, transform, and prepare data for analysis.
  • Development: Gain insights into efficient and maintainable code development practices.
  • Data Modelling: Master techniques for structuring data effectively.
  • Data Solution Design: Develop robust and scalable data solutions.
  • Software Design: Understand the principles of good software architecture for data projects.
  • Unit Testing & Troubleshooting: Ensure data quality and quickly resolve issues.

We follow a natural project lifecycle approach, demonstrating these concepts through a blend of engaging lectures, practical screencasts, interactive quizzes, and hands-on exercises. You'll work with practical retail data using Python and Jupyter Notebooks to solidify your understanding.

Important Note: While Jupyter Notebooks are used for practical illustration, the focus is on understanding the techniques and why they're important, not specific implementation within the notebook environment. These techniques can be applied using other software. Hands-on exercises are beneficial but not mandatory.

This course bridges the gap between specialized courses in programming, data analysis, and data modelling. You'll gain a critical understanding of your current data environment and develop a more thoughtful approach to data-related tasks.

Ultimately, this course equips you with a more complete understanding of data projects, transforming you into a more effective and well-rounded data professional. Prepare to think critically and approach your work with greater confidence!

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