Description
Data Analysis, Simulation, Visualization and Exploration course. This course is a comprehensive, hands-on training that teaches data analysis, simulation, visualization, and exploration skills using core Python libraries including NumPy, Pandas, Matplotlib, and Seaborn. The course is designed with a focus on hands-on learning through problem-solving and project-based learning, preparing participants to become experts in these fields. The course provides the practical knowledge needed and covers a wide range of key concepts such as Monte Carlo simulation, time series analysis, and image processing. The ultimate goal of this course is to strengthen Python programming skills and its effective application in the fields of engineering, statistics, computer science, and business analytics.
What you will learn
- Introduction to Python and NumPy:
- Mastery of Python data types and the NumPy library.
- Learn the basics and principles of Python.
- Data analysis with Pandas:
- Gain deep expertise in the Pandas library to learn data analysis techniques.
- Learn Pandas Series, Pandas Data Frames, groupby method, pivot table, conditional filtering with Pandas, combining Data Frames, and other advanced data analysis techniques.
- Data visualization with Matplotlib:
- Master Matplotlib, the most powerful Python library for plotting and data visualization.
- Learn how to customize shapes and charts from 1D to 3D.
- Learn advanced customizations such as subplots, styling, and object-oriented programming with Matplotlib.
- Visualization and inference with Seaborn:
- Gain deep expertise in Seaborn, a library for data visualization and inference.
- Learn Scatterplots, Cluster Charts, Distribution Charts, Comparison Charts, Seaborn Grids, Pie Charts, and Matrix Charts.
- Presenting graphs, charts, and visualizations in a way that, in addition to visualization, can also infer statistical information such as data distribution, mean, median, and interquartile range.
- Visual and data analysis project:
- Learn data analysis and visual analytics by completing a project that applies knowledge gained from Pandas, Matplotlib, and Seaborn.
- Monte Carlo simulation and visualization:
- Learn Monte Carlo simulation and visualization with lots of experiments and exercises.
- Conducting numerous Monte Carlo simulation experiments.
- Creating and visualizing time series:
- Learn to create and visualize different types of time series data such as impulse, quadratic, triangular, sinusoidal, and hybrid time series to simulate real-world data.
- Creating and visualizing images:
- Learn how to create your own color and black and white images.
- Learn how to draw lines, edges, corners, loops, and circles on images.
- Learn how to create your own custom image datasets.
This course is suitable for people who:
- Data Scientists who want to learn data analysis and visualization tools.
- Anyone who wants to learn how to simulate and visualize data.
- Anyone who wants to improve their Python programming skills.
- Engineers.
- Statisticians.
- Computer scientists.
- Business Analysts.
Course details
- Publisher: Udemy
- Instructor: Zeeshan Ahmad
- Training level: Beginner to advanced
- Training duration: 17 hours and 12 minutes
- Number of lessons: 119
Course syllabus as of 2025/1
Prerequisites for the Data Analysis Simulation Visualization and Exploration course
- High school mathematics is recommended but not necessary
Course images
Sample course video
Installation Guide
After Extract, view with your favorite player.
Subtitles: None
Quality: 720p
Download link
Downloadly
Rapidgator link
File(s) password: www.downloadly.ir
File size
5.3 GB
