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⇱ Data Analytics with Python | Coursera

Data Analytics with Python

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Data Analytics with Python

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Gain insight into a topic and learn the fundamentals.
4.9

22 reviews

Beginner level

Recommended experience

5 hours to complete
Flexible schedule
Learn at your own pace
Gain insight into a topic and learn the fundamentals.
4.9

22 reviews

Beginner level

Recommended experience

5 hours to complete
Flexible schedule
Learn at your own pace

What you'll learn

  • Master Python basics, including syntax and real-world applications

  • Use NumPy, Pandas, and Matplotlib for data analysis and visualization

  • Solve practical problems and work with real-world datasets effectively

  • Build a strong foundation for advanced programming and data-driven tasks

Details to know

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Assessments

2 assignments

Taught in English

There are 2 modules in this course

This Data Analytics with Python course offers a comprehensive journey into mastering programming and data analysis. Start with an introduction to Python, exploring its syntax, versatility, and real-world applications in data science, web development, and automation. Dive into powerful libraries like NumPy for numerical computing, Pandas for data manipulation, and Matplotlib for creating compelling visualizations. Gain hands-on experience solving practical problems and working with real-world datasets to enhance your programming skills. Learn to leverage Python’s capabilities for data-driven tasks and computational efficiency, preparing you for success across diverse industries.

By the end of this course, you will: - Understand Python fundamentals, syntax, and real-world applications. - Utilize NumPy, Pandas, and Matplotlib for data analysis and visualization. - Solve practical problems and work with real-world datasets. - Build a strong foundation for programming and computational tasks. Ideal for beginners and professionals looking to unlock Python's potential for data analysis, visualization, and automation.

This comprehensive Data Analytics with Python course will equip you with the essential skills to program, analyze, and visualize data effectively. You’ll start by mastering Python fundamentals, including syntax and real-world applications in fields like data science, web development, and automation. Explore powerful libraries such as NumPy for numerical computing, Pandas for data manipulation, and Matplotlib for creating stunning visualizations. Gain hands-on experience solving practical problems and working with real-world datasets to enhance your programming capabilities. Perfect for beginners and professionals aiming to unlock Python’s potential for impactful data analysis and decision-making.

What's included

7 videos2 readings1 assignment

7 videos•Total 61 minutes
  • Data Analytics with Python•2 minutes
  • Python Libraries•7 minutes
  • Python•8 minutes
  • Slicing•14 minutes
  • Head of the data•10 minutes
  • Functionality•11 minutes
  • DataFrame•8 minutes
2 readings•Total 20 minutes
  • Course Syllabus•10 minutes
  • Data Analytics with Python•10 minutes
1 assignment•Total 50 minutes
  • Assessment for Data Analytics with Python•50 minutes

Master data visualization with Matplotlib and Pandas, using advanced techniques to analyze and present data.

What's included

8 videos1 assignment

8 videos•Total 100 minutes
  • Matplotlib Tutorial•9 minutes
  • Operator Description•12 minutes
  • Features•9 minutes
  • Tiny dot•13 minutes
  • Cumulative Detailed Histogram: Part 1•15 minutes
  • Cumulative Detailed Histogram: Part 2•14 minutes
  • Working with Pandas•14 minutes
  • Imported Data set•14 minutes
1 assignment•Total 60 minutes
  • Assessment for Data Visualization and Analysis with Matplotlib and Pandas•60 minutes

Instructor

Instructor ratings
4.8 (8 ratings)
Simplilearn
23 Courses•28,092 learners

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Frequently asked questions

Yes, Python is excellent for data analytics due to its robust libraries like Pandas, NumPy, and Matplotlib, which simplify data manipulation, analysis, and visualization.

The best Python course for data analysts covers Python basics, data manipulation with Pandas, data visualization with Matplotlib/Seaborn, and hands-on projects for practical experience.

The 7 steps are: defining the question, collecting data, cleaning data, exploring data, performing analysis, interpreting results, and presenting findings.

Yes, Python is a valuable skill for data analysts, enabling efficient data manipulation, analysis, and visualization for actionable insights.

Anyone with analytical skills, knowledge of statistics, and tools like Python, Excel, or SQL can become a data analyst. A background in math, computer science, or related fields is beneficial.

To access the course materials, assignments and to earn a Certificate, you will need to purchase the Certificate experience when you enroll in a course. You can try a Free Trial instead, or apply for Financial Aid. The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.

When you purchase a Certificate you get access to all course materials, including graded assignments. Upon completing the course, your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile.

Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.

Financial aid available,