Data Analysis Project in Python

Create Data Analysis Project with Python, Pandas, Numpy, Matplotlib, Seaborn,Plotly.

Language: english

Note: 4.6/5 (12 notes) 2,443 students New course

Instructor(s): Nethra B

Last update: 2022-06-21

What you’ll learn

Define the roles and responsibilities of DATA ANALYST
Able to come up with solution to real world data analysis work
Become comfortable with python and its libraries.
Confidently apply for a Data analyst position

Requirements

Basic of Python is required. (not mandatory). But we start from scratch, so that it will be beneficial for non coding background students.

Description

In this course you will create data analyst portfolio project using real world data set from kaggle.

If you are from non technical background or fresher who wants to do career transition then Data Analyst will be easier path to take and then you can explore yourself with the data science.

Even as a Data scientist , you spend most of your time in understanding the data , cleaning the data modifying the Data as per the requirements.

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Explanation : I have explained every single line of code in this course to make it easy for the beginners.

Query Resolution : I will resolve your queries with in 24 Hrs.

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By the end of this course You will be able comfortable with python and some commonly sued libraries by a Data Analyst and you will be able to confidently apply for Data Analyst role.

Data Analyst role also require you to know SQL which is not covered in this course.

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About My Self :

I’m Nethra. Looking to learn Data Analysis ? Let me help you. I am working as Senior Data Analyst with 8 Years of Experience. I have designed few courses with real world cases, not to teach just basics. Hopefully my videos will be helpful to you in your journey.

Thank you

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Who this course is for

Anyone who is interested in career transition towards Data Analysis

Course content

Case Study 2 : Hotel Booking Analysis
- Dataset
- Understanding the Data
- Preparing the Data for Analysis
- Where do Guest Come From?
- Room Price Analysis
- Room Price Analysis Across Room Type
- How Long Do Guest Stay
- Booking By Market segment
- Booking Cancellation
- Conclusion