Learn data analytics and visualisation with Pandas and Matplotlib
In this Data Analytics and Visualisation with Python course, you will learn basic concepts of data analytics and data visualisation utilising several different Python libraries such as Pandas mainly for reading our dataset and performing statistical calculations whilst Matplotlib mainly for data visualisation, including but not only limited to generating scatter plot and bar plot. We will obtain our datasets from Kaggle data bank and later on in this course, we will also discuss Kaggle data competition as our learning motivations. Since this course was designed for beginners, hence, I tried my best to teach and explain all materials from the perspective of someone who has limited knowledge in Python and data analytics. As the nature of this course which was intended for beginner, it will not make you an expert in a night, instead, it will provide you a strong and solid understanding of data analytics concepts, multiple different statistical methods like mean, max, min, median, mode, as well as be comfortable operating Pandas and Matplotlib which hopefully enables you to start experimenting, exploring and building your data analytics portfolio. Last but not least, this course will also train you to have a mindset that needs to be had by a professional data practitioner, understanding data analytics cycle and data acumen which in my personal opinion are very important skills to be had enabling you to communicate your solution with others who come from non technical background.
What you’ll learn
- Learn basic data analytics and data visualisation concepts.
- Be familiar to use Pandas and Matplotlib.
- Learn how to perform statistical analysis on dataset.
- Learn how to generate scatterplot and bar plot.
- Learn how to explore datasets on Kaggle.
Course Content
- Introduction to Data Analytics and Visualisation with Python –> 2 lectures • 12min.
- Let’s begin our journey! –> 3 lectures • 20min.
- Google Colab Set Up –> 1 lecture • 5min.
- Dataset 1 Practice –> 3 lectures • 59min.
- Dataset 2 Practice –> 4 lectures • 56min.
- Data Analytics Common Practice Guide –> 1 lecture • 8min.
- Kaggle Data Competition –> 1 lecture • 10min.
Requirements
In this Data Analytics and Visualisation with Python course, you will learn basic concepts of data analytics and data visualisation utilising several different Python libraries such as Pandas mainly for reading our dataset and performing statistical calculations whilst Matplotlib mainly for data visualisation, including but not only limited to generating scatter plot and bar plot. We will obtain our datasets from Kaggle data bank and later on in this course, we will also discuss Kaggle data competition as our learning motivations. Since this course was designed for beginners, hence, I tried my best to teach and explain all materials from the perspective of someone who has limited knowledge in Python and data analytics. As the nature of this course which was intended for beginner, it will not make you an expert in a night, instead, it will provide you a strong and solid understanding of data analytics concepts, multiple different statistical methods like mean, max, min, median, mode, as well as be comfortable operating Pandas and Matplotlib which hopefully enables you to start experimenting, exploring and building your data analytics portfolio. Last but not least, this course will also train you to have a mindset that needs to be had by a professional data practitioner, understanding data analytics cycle and data acumen which in my personal opinion are very important skills to be had enabling you to communicate your solution with others who come from non technical background.