Data Analytics and Visualisation with Python

Data Analytics and Visualisation with Python, available at $59.99, has an average rating of 4.1, with 17 lectures, based on 21 reviews, and has 3643 subscribers.

You will learn about 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 This course is ideal for individuals who are Python beginners who are interested in data analytics or Entry level job seekers who want to build up their data analytics and visualisation portfolio It is particularly useful for Python beginners who are interested in data analytics or Entry level job seekers who want to build up their data analytics and visualisation portfolio.

Enroll now: Data Analytics and Visualisation with Python

Summary

Title: Data Analytics and Visualisation with Python

Price: $59.99

Average Rating: 4.1

Number of Lectures: 17

Number of Published Lectures: 17

Number of Curriculum Items: 17

Number of Published Curriculum Objects: 17

Original Price: $22.99

Quality Status: approved

Status: Live

What You Will 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

Who Should Attend

Python beginners who are interested in data analytics

Entry level job seekers who want to build up their data analytics and visualisation portfolio

Target Audiences

Python beginners who are interested in data analytics

Entry level job seekers who want to build up their data analytics and visualisation portfolio

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.

Course Curriculum

Chapter 1: Introduction to Data Analytics and Visualisation with Python

Lecture 1: Introduction: Welcome to Data Analytics and Visualisation Course

Lecture 2: Whom the course is intended for?

Chapter 2: Lets begin our journey!

Lecture 1: Introduction to Kaggle

Lecture 2: Tools, Python libraries, and datasets preparation

Lecture 3: Lets get started: exploring and picking datasets from Kaggle

Chapter 3: Google Colab Set Up

Lecture 1: Set Up your Google Colab

Chapter 4: Dataset 1 Practice

Lecture 1: Dataset 1: get overview of the dataset

Lecture 2: Dataset 1: practice part 1

Lecture 3: Dataset 1: practice part 2

Chapter 5: Dataset 2 Practice

Lecture 1: Dataset 2: get overview of the dataset

Lecture 2: Dataset 2: practice part 1

Lecture 3: Dataset 2: practice part 2

Lecture 4: Dataset 2: practice part 3

Chapter 6: Data Analytics Common Practice Guide

Lecture 1: Data Analytics Common Practice Guide

Chapter 7: Kaggle Data Competition

Lecture 1: Kaggle Data Competition: How to Participate?

Chapter 8: Cleaning Dataset

Lecture 1: Cleaning Dataset by Removing Missing Values & Duplicate Values

Lecture 2: Detecting Potential Outliers with IQR

Instructors

Christ Raharja
Ex Technology Risk Consultant, and E-commerce enthusiast

Rating Distribution

1 stars: 0 votes

2 stars: 2 votes

3 stars: 4 votes

4 stars: 6 votes

5 stars: 9 votes

Frequently Asked Questions

How long do I have access to the course materials?

You can view and review the lecture materials indefinitely, like an on-demand channel.

Can I take my courses with me wherever I go?

Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!