Data Analytics and Visualisation with Python
What you'll learn
- Learn basic data analytics and data visualisation concepts
- Be how to perform extensive analysis using Pandas
- Learn how to perform data visualisation using Matplotlib
- Learn how to visualize data using scatterplot and bar plot
- Learn how to find and download datasets from Kaggle
- Learn how to clean dataset by removing missing values and duplicate values
- Learn how to detect potential outliers using IQR
Requirements
- Basic knowledge and understanding in Python
- Basic knowledge and understanding in statistics
- No advanced programming skill is required
Description
Welcome to the Data Analytics and Visualization with Python Course!
Are you ready to embark on a comprehensive journey into the realm of data analytics and visualization using Python, tailored for the Udemy marketplace? This course is thoughtfully designed to equip you with fundamental concepts and practical skills that are essential for beginners and aspiring data enthusiasts.
Course Highlights:
Module 1: Introduction to Data Analytics and Python
Gain a solid introduction to the field of data analytics.
Learn how to leverage Python, one of the most popular programming languages in data analysis.
Module 2: Data Handling with Pandas
Dive into the power of Pandas, a versatile library for data manipulation.
Discover how to read and preprocess datasets effectively.
Perform essential statistical calculations to derive insights from your data.
Module 3: Data Visualization with Matplotlib
Unlock the potential of Matplotlib for data visualization.
Explore various visualization techniques, including scatter plots and bar plots.
Transform raw data into insightful visual representations.
Module 4: Kaggle Data Exploration
Access Kaggle's vast data repository and leverage real-world datasets.
Discuss Kaggle data competitions as a source of motivation and learning.
Apply your newfound skills to analyze Kaggle datasets and tackle data challenges.
Module 5: Beginner-Friendly Approach
Designed with beginners in mind, this course explains concepts in a clear and accessible manner.
Learn Python and data analytics from scratch, with no prior experience required.
Module 6: Building Strong Foundations
Understand key statistical methods, including mean, max, min, median, and mode.
Become proficient in using Pandas and Matplotlib, setting the stage for further exploration.
Module 7: Data Cleaning and Preprocessing
Explore advanced data preprocessing techniques.
Learn to identify and handle duplicate entries, missing values, and potential outliers using the Interquartile Range (IQR) method.
Who this course is for:
- Python beginners who are interested in data analytics
- Entry level job seekers who want to build up their data analytics and visualisation portfolio
Instructor
- 4.0 Instructor Rating
- 2,035 Reviews
- 96,138 Students
- 117 Courses
Hi all, my name is Chris Raharja. I graduated from University of Washington with BS in Mathematics. I used to work as a technology consultant in one of Big 4 firms and now I have been running several different business models such as print on demand, affiliate marketing, drop shipping, ads traffic arbitrage. I have been always passionate about teaching since my first time as a volunteer math tutor in high school. My goal on Udemy is to share my knowledge and build a wonderful community to study many different things together.