About This Course
This Python Data Expert course will provide a comprehensive overview of Python data types, data structures, NumPy, Pandas, advanced Python, and advanced Pandas. This course is designed to help you become a data expert by learning to manipulate, analyze, and visualize data using the most up-to-date tools available. You will gain a deep understanding of data structures and data types, and learn to use NumPy and Pandas to explore and manipulate data. Additionally, you will gain an understanding of advanced Python and advanced Pandas techniques that will help you to become a data scientist. However, this course will not cover topics such as data visualization and machine learning.
Learning Objectives
Material Includes
- Datasets
Requirements
- 1. Install Python on your computer, preferably the latest stable version, and set up an Integrated Development Environment (IDE) such as PyCharm or Jupyter Notebook.
- 2. Familiarize yourself with essential Python libraries for data manipulation and analysis, such as NumPy and Pandas. Install these libraries using the appropriate package manager, like pip.
- 3. Access the course materials, whether they are provided in a textbook, online platform, or through downloadable resources. Make sure you have a reliable internet connection for accessing additional resources and documentation.
- 4. Follow along with the course exercises and examples, working through the coding tasks and practice problems. Take time to understand the concepts and experiment with the code to solidify your understanding.
- 5. Engage actively with the course content by asking questions, seeking clarification when needed, and practicing regularly. Make use of online forums, coding communities, and tutorials to supplement your learning and deepen your understanding of Python data manipulation and analysis.
- Remember, consistent practice, hands-on experimentation, and an inquisitive mindset are key to mastering Python for data analysis. Enjoy the learning process and don't hesitate to seek help when needed!
Target Audience
- 1. Data scientist enthusiasts
- 2. Beginner Python developers
- 3. Computer science students specializing in data analysis
- 4. Experienced data analysts seeking advanced Python skills
- 5. IT professionals interested in data manipulation and analysis
- 6. Enthusiastic individuals looking to explore data science with Python
- 7. Experienced Python developers transitioning into the data field
- 8. Researchers working with large datasets and seeking Python proficiency
- 9. Business analysts seeking to enhance their data analysis capabilities with Python
- 10. Statisticians interested in leveraging Python for data manipulation and visualization.
Curriculum
Getting Started with Python
Introduction
Python arithmetic
Basic data types
PDE001
Python Data Structures
Numpy & Pandas
Advanced Python
Advanced Pandas
Your Instructors
Edulearnia
R&D Engineer
I am in love with artificial intelligence, machine learning, deep learning and especially data science. I like challenges and a job well done. I am sure to participate in the local and international development of artificial intelligence. I like reading, writing, soft music. I like to be in a friendly relationship with my entourage, I like to be helpful.
Material Includes
- Datasets
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