What you'll get
- 15+ Hours
- 5 Courses
- Mock Tests
- Course Completion Certificates
- Self-paced Courses
- Technical Support
- Case Studies
Synopsis
- Understanding Python as a general-purpose programming language for websites, software, automation, and data analysis.
- The importance of Python across domains like AI, finance, web development, and data science.
- Learning Python's simple syntax and readability for frameworks such as Flask and Django, as well as data science and machine learning applications.
- Installing Anaconda Distribution on Windows, macOS, and Linux.
- Overview of Jupyter Notebook and Jupyter Lab for coding and project development.
- Introduction to Python programming and the first steps in coding.
- Correct usage of quotation marks in Python coding.
- Understanding coding form and style best practices.
- Introduction to basic data structures in Python.
- Performing variable assignments, including complex assignments for efficient programming.
Content
| Courses | No. of Hours | Certificates | Details |
|---|---|---|---|
| Pandas with Python Tutorial | 5h 42m | ✔ | View Curriculum |
| Numpy and Pandas | 5h 9m | ✔ | View Curriculum |
| Data Analysis with Pandas and Python | 59m | ✔ | View Curriculum |
| Pandas Project | 3h 14m | ✔ | View Curriculum |
| Analyzing the Quality of White Wines Using NumPy | 1h 22m | ✔ | View Curriculum |
| Courses | No. of Hours | Certificates | Details |
|---|---|---|---|
| No courses found in this category. | |||
Description
The Data Analysis with NumPy and Pandas course introduces learners to two of Python's most powerful libraries for data analysis. NumPy and Pandas provide comprehensive tools for handling large datasets—enabling tasks such as analyzing, organizing, sorting, filtering, pivoting, aggregating, cleaning, and calculating, among others.
This course guides learners step-by-step through installation, data manipulation, and visualization, covering hundreds of methods, attributes, and features within these libraries. Students will work with a wide variety of datasets—short or long, clean or messy—to explore the versatility and efficiency of NumPy and Pandas.
Designed as a hands-on, project-based course, learners will take on the role of a Data Analyst, applying Python skills to analyze products, pricing, transactions, and other real-world data. The course includes dozens of datasets for practice, ensuring learners gain practical experience while mastering these essential data analysis tools.
Requirements
- A working computer with Windows, Mac, or Linux.
- No prior knowledge of Python is required; the course is suitable for beginners.
- Motivation to learn Python, the programming language with one of the highest numbers of job opportunities.
- Interest in machine learning using Python.
- Curiosity and enthusiasm for Python programming.
- Willingness to learn Python, PyCharm, and Python development workflows.
Target Audience
- Beginners who want to start a Python bootcamp.
- Individuals planning a career as a Python developer or in data analysis.
- Learners interested in Python programming, coding examples, and development.
- Those focused on big data, machine learning, and data science.
- Anyone looking to master the Pandas library and improve Python skills.
