Python for Data Analysis with Practical Projects

Name: Python for Data Analysis with Practical Projects
Rating: 4.6 (11 reviews)

Learn Data Analysis with Projects in Python using Seaborn,Pandas,Plotly, Numpy and become expert Data Analyst

Created byManuel Ernesto Cambota

Last updated 6/2024

English

What you'll learn

Data Handling: Master data cleaning, manipulation, and transformation techniques.
Visualization: Create insightful visualizations to communicate data-driven insights effectively
Statistical Analysis: Perform basic statistical analysis and draw meaningful conclusions from data
Project Portfolio: Build a portfolio of projects showcasing your skills to potential employers or for personal growth.

Course content

6 sections • 39 lectures • 6h 47m total length

Overview8:32
Installation of Anaconda Navigator2:18

Collect Data for Analysis8:48
collect data with pandas and numpy; read multiple csv files, handle paths with raw strings, concatenate into a final data frame for analysis, and support visualizations with matplotlib and seaborn.
Data preparation7:33
Analysing Trips of Uber8:37
Analysing Monthly rides9:50
Analysing demand of Ubers8:20
Performing Cross Analysis11:50
Perform Spatial Analysis on Demand of Uber15:20
Analysing Uber Pickups in Each month9:27
Analysing Rush in New York City7:53
Perform In-Depth Analysis of Uber Base Number10:21

Reading Data from SQLite Database10:22
Perform Sentment Analysis on Data17:06
How Amazon recommend product13:31
Analysing Feedback given by Customers8:08
Preparing Data for Analysis15:43
Prepare and clean data by converting text to lowercase, removing punctuation and stop words, and applying custom rules to enable accurate sentiment analysis and feature exploration.
Analysing Behaviour of Customers12:32

Prepare your Data for the Analysis7:35
Analysing Total cases, Deaths, Recovered & active cases10:51
Analyze covid-19 data to identify top countries by total cases, deaths, recovered, and active cases using a plotly treemap and track trends with a line plot over date.
Perform EDA on Data9:14
Explore exploratory data analysis and visualization to compute population to test done ratio and compare deaths, recovered, and active cases across top 20 countries with bar and stacked charts.
Analysing those countries that gets badly affected by Corona11:54
Perform In-depth Analysis on Data14:42
Automate Your Analysis12:50

Perform descriptive Analysis on Data9:47
Perform descriptive analysis on a bank personal loan dataset by reading data, preprocessing and removing id and zip code, and using five-point summaries and box plots to reveal distributions.
Understanding Data Pre-processing12:12
Develop data pre-processing skills by visualizing distributions via histograms, checking skewness with pandas, and cleaning data: impute negative experience values with the mean using numpy where and prepare for analysis.
Analysing Education Satus of Costumers9:39
Analyze correlations with a heat map and mitigate multicollinearity by dropping the experience column. Map education codes to labels and visualize education status among loan applicants with plotly pie chart.
Analysing Account holder distribution7:26
Automate your Analysis14:34
Analyse Customer Behaviour on the basis of several attributes5:03
Iterate over the data frame columns such as security account, online, account holder category, and credit card to generate count plots by personal loan, automating category analysis.
Perform Hypothesis on Data16:17

Requirements

No Pre-requisites

Description

Unlock the power of Python for data analysis through practical projects tailored for beginners. Whether you're looking to enter the world of data science or enhance your analytical skills, this course is designed to equip you with essential Python tools and techniques.

Course Overview:

Learn by Doing: Dive straight into hands-on projects that simulate real-world data scenarios. From data cleaning and manipulation to visualization and statistical analysis, every project builds your skills incrementally.
Comprehensive Guidance: Benefit from clear, step-by-step instructions and explanations. Our expert instructors ensure you understand the concepts behind each technique, empowering you to apply them confidently.
Practical Skills: Gain proficiency in popular Python libraries such as Pandas, NumPy, and Matplotlib. By the end of the course, you'll be proficient in handling and analyzing data efficiently.

Why Choose this Course?

Beginner-Friendly: No prior coding experience required. We start with the basics and gradually introduce more advanced topics, making learning accessible for everyone.
Career-Ready: Equip yourself with skills sought after in today's data-driven world. Whether you're a student, professional, or career changer, this course enhances your employability.
Supportive Community: Join a vibrant community of learners. Get support from the instructor, share insights, and collaborate on projects to reinforce your learning.

Whether you're driven by curiosity or career ambitions, Python for Data Analysis with Projects for Beginners is your gateway to mastering data analysis with Python. Enroll now and embark on a transformative learning experience that opens doors to new opportunities in data science and beyond.

Who this course is for:

Beginners in Data Analysis: If you're new to data analysis and want to learn how to use Python for handling and analyzing data, this course provides a solid foundation.
Students: Whether you're studying data science, statistics, or a related field, mastering Python for data analysis will complement your academic journey.
Professionals: If you're looking to upskill or transition into a data-focused role, this course equips you with practical skills that are in demand across industries.
Career Changers: If you're considering a career shift into data analysis or data science, this course offers a structured pathway to build essential skills and create a portfolio of projects.
Anyone Interested in Data: If you're curious about how data drives decisions and want to learn how to extract insights from data using Python, this course provides a beginner-friendly introduction.

Python for Data Analysis with Practical Projects

What you'll learn

Explore related topics

Course content

Introduction2 lectures • 11min

Project 1 - Data Analisys for Uber10 lectures • 1hr 38min

Project 2 - Hotel Booking8 lectures • 1hr 20min

Project 3 - Data Analysis for Amazon Customers6 lectures • 1hr 17min

Project 4 - Data Analysis for Covid-196 lectures • 1hr 7min

Project 5 - Finance Data Analysis7 lectures • 1hr 15min

Requirements

Description

Who this course is for: