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Data Programming

Numpy

Adedigbadeola@gmail

Welcome to Realcare Tech Mark's Online NumPy Course, your gateway to mastering the powerful numerical computing library in Python. Whether you're a data scientist, engineer, or enthusiast, this course is crafted to enhance your skills in handling large datasets, performing mathematical operations, and manipulating numerical arrays efficiently using NumPy.

Curriculum

10 Sections
30 Lessons
0 Quizzes
0 Google Meets
0m Duration

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Introduction to NumPy

3 Lessons0 Quizzes0 Google Meets

Overview of NumPy and its Applications
Installation and Setup
Basic NumPy Concepts

NumPy Arrays

3 Lessons0 Quizzes0 Google Meets

Creating NumPy Arrays
Indexing and Slicing
Array Manipulation

Array Operations

3 Lessons0 Quizzes0 Google Meets

Element-Wise Operations
Linear Algebra Operations
Statistical Operations

Broadcasting

3 Lessons0 Quizzes0 Google Meets

Understanding Broadcasting
Practical Applications
Tips for Efficient Broadcasting

File Input/Output with NumPy

3 Lessons0 Quizzes0 Google Meets

Reading and Writing Data with NumPy
Compatibility with Different File Formats
Handling Large Datasets

Advanced NumPy Features

3 Lessons0 Quizzes0 Google Meets

Masked Arrays
Universal Functions (ufuncs)
Memory Management in NumPy

NumPy and Data Science

3 Lessons0 Quizzes0 Google Meets

Data Preprocessing with NumPy
Analyzing Data Using NumPy
Integration with Other Data Science Libraries

NumPy and Machine Learning

3 Lessons0 Quizzes0 Google Meets

Feature Engineering with NumPy
Data Transformation for ML
Evaluating Models with NumPy

Optimizing NumPy Code

3 Lessons0 Quizzes0 Google Meets

Vectorization for Performance
Parallel Computing with NumPy
Best Practices in NumPy Optimization

Practical Applications

3 Lessons0 Quizzes0 Google Meets

Applying NumPy to Real-World Projects
Building a Portfolio of NumPy Applications
Showcasing Your NumPy Skills

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Last Updated: March 15, 2024

This course includes

Dive into the core of NumPy
Exploration of arrays
Statistical calculations
Introduction to NumPy: Understand the fundamentals of NumPy, its role in scientific computing, and its advantages in numerical operations.
NumPy Arrays: Dive into the core of NumPy with a comprehensive exploration of arrays, array creation, indexing, and slicing.
Array Operations: Learn to perform essential mathematical operations on arrays, including element-wise operations, linear algebra operations, and statistical calculations.
Broadcasting: Explore the concept of broadcasting to efficiently operate on arrays of different shapes without the need for explicit looping.
File Input/Output with NumPy: Gain practical skills in reading and writing data from/to files using NumPy, supporting seamless integration with external datasets.
Advanced NumPy Features: Delve into advanced features such as masked arrays, ufuncs, and memory management for optimal performance.
NumPy and Data Science: Understand the role of NumPy in data science workflows, including data preprocessing, analysis, and integration with other libraries.
NumPy and Machine Learning: Explore how NumPy is used in machine learning tasks, including feature engineering, data transformation, and model evaluation.
Optimizing NumPy Code: Learn techniques to optimize your NumPy code for better performance, including vectorization and parallel computing.
Practical Applications: Apply your NumPy skills to real-world scenarios and projects, reinforcing your understanding and building a strong foundation for future endeavors.

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