Python | Data Analysis | Jupyter Notebook
Description
Python is the fastest growing Data Analytics Programming Languages. This course provides you with foundational knowledge of Python and introduces you to analyzing data using Python.
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Knowing Python is highly important if you intend working with data and the demand for professionals with Python skills is ever growing.
You will learn Python in a practical way using Jupyter notebook.
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You will work on a guided project that you can share with family and friends using all the topics covered in this course
This course is hands-on with practice tasks which allows you get comfortable and familiar with coding in Python.
Content of This Course Includes:
Python as a Programming Language, Data Types, Variables, Operators, Numbers in Python, String Data Type, String Methods, Slicing, Functions, Casting Variables.
You will also learn about what you need to get into a data related career.
Course Requirement or Prerequisites
This course does not require any prior knowledge or specific academic background. The only requirement is having a laptop or desktop computer. All applications necessary for learning the course would be downloaded free from the internet.
Who is this course for?
Anyone looking to work with data personally or professionally.
Looking into a career as Data Analyst, Data Scientist, Business Analyst, Report Analyst, ETL Specialist, BI Consultant, Data Engineer or any Data related field.
| Total Students | 6002 |
|---|---|
| Duration | 1.5 hours |
| Language | English (US) |
| Number of lectures | 7 |
| Number of quizzes | 0 |
| Total Reviews | 180 |
| Global Rating | 4.07 |
| Instructor Name | Alexander Shafe |
Course Insights (for Students)
Actionable, non-generic pointers before you enroll
Student Satisfaction
78% positive recent sentiment
Momentum
Steady interest
Time & Value
- Est. time: 1.5 hours
- Practical value: 7/10
Roadmap Fit
- Beginner → Beginner → Advanced
Key Takeaways for Learners
- Analytics
- Hands On
- Beginner Friendly
Course Review Summary
Signals distilled from the latest Udemy reviews
What learners praise
- Hands On
- Beginner Friendly
- Clear Explanation
- Project
- Real World
Watch-outs
- Too fast
- Too slow
- Theory only
Difficulty
Best suited for
New learners starting from zero, Doers who prefer project-led learning
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