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Course Outline
Module I: NumPy – Working with Array Data
1. Creating vectors and matrices using `numpy.array`
2. Array shapes, changing dimensions, data size
3. Basic array operations – indexing, slicing, broadcasting
4. Mathematical functions – element-wise operations
5. Aggregations and statistics (sum, mean, std, etc.)
Module II: Pandas – Tabular Data and Processing
1. Basic data structures: `Series` and `DataFrame`
2. Loading data from `.csv` files
3. Exploring DataFrames – head, describe, info
4. Filtering records and selecting columns
5. Modifying data: adding, deleting, and transforming columns
6. Creating new columns based on existing data
7. Sorting and ordering data
8. Grouping and aggregations
9. Working with large datasets – chunking, data type optimization
Module III: Data Visualization – Matplotlib and Seaborn
1. Differences between matplotlib and seaborn – when to use each library
2. Key types of plots
3. Configuring and styling plots – axes, legends, colors, sizes
4. Creating plots using data from Pandas
Module IV: Exploratory Data Analysis (EDA)
1. Introduction to EDA – goals and analysis process
2. Example analysis on a real dataset
3. Practical project
21 Hours
Testimonials (4)
Hands-on examples allowed us to get an actual feel for how the program works. Good explanations and integration of theoretical concepts and how they relate to practical applications.
Ian - Archeoworks Inc.
Course - ArcGIS Fundamentals
All the topics which he covered including examples. And also explained how they are helpful in our daily job.
madduri madduri - Boskalis Singapore Pte Ltd
Course - QGIS for Geographic Information System
I really enjoyed the training. I found all modules to be applicable to problems that I am trying to solve at work. The integration of the training with jupyter notebooks was really impressive.
Mark Firmin - Environment and Climate Change Canada
Course - Python for Geographic Information System (GIS)
Real world knowledge from someone in the industry
