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NumPy Mega Course

Your complete NumPy journey: Beginner to expert, zero to hero!

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NumPy Mega Course

6 Modules

Course Curriculum

6 Modules · 23 Chapters · 23 Topics · 173 Sub-topics

Introduction to NumPy

1 Topics

NumPy Fundamentals

5 Sub-topics

What is NumPy and Why Use It

Installing NumPy

Importing NumPy

NumPy vs Python Lists

Understanding ndarray Object

NumPy Array Fundamentals

1 Topics

Array Basics

6 Sub-topics

Creating 1D Arrays

Creating 2D Arrays

Creating 3D Arrays

Array Attributes - shape, size, ndim

Array Attributes - dtype and itemsize

Checking Array Type

Array Creation Methods

1 Topics

Array Creation Techniques

10 Sub-topics

Creating Arrays with np.array()

Creating Arrays with np.zeros()

Creating Arrays with np.ones()

Creating Arrays with np.empty()

Creating Arrays with np.full()

Creating Identity Matrices - np.eye() and np.identity()

Creating Arrays with np.arange()

Creating Arrays with np.linspace()

Creating Arrays with np.logspace()

Creating Arrays from Existing Data

Array Indexing and Slicing

1 Topics

Accessing Array Elements

9 Sub-topics

Basic Indexing in 1D Arrays

Basic Indexing in 2D Arrays

Basic Indexing in 3D Arrays

Negative Indexing

Slicing 1D Arrays

Slicing 2D Arrays - Rows and Columns

Slicing with Step Values

Slicing Multi-dimensional Arrays

Understanding Views vs Copies

Array Manipulation Part 1

1 Topics

Reshaping and Transforming Arrays

6 Sub-topics

Reshaping Arrays - reshape()

Flattening Arrays - flatten() and ravel()

Transposing Arrays

Swapping Axes

Adding Dimensions - np.newaxis

Squeezing Dimensions

Array Manipulation Part 2

1 Topics

Combining and Splitting Arrays

6 Sub-topics

Concatenating Arrays - concatenate()

Stacking Arrays - vstack and hstack

Stacking Arrays - dstack and stack

Splitting Arrays - split, vsplit, hsplit

Repeating Arrays - repeat and tile

Inserting and Deleting Elements

Array Operations Part 1

1 Topics

Basic Array Operations

7 Sub-topics

Element-wise Addition

Element-wise Subtraction

Element-wise Multiplication

Element-wise Division

Floor Division and Modulo

Exponentiation

Square Root and Power Functions

Array Operations Part 2

1 Topics

Advanced Array Operations

5 Sub-topics

Comparison Operators

Logical Operations - AND, OR, NOT

Universal Functions (ufuncs) Overview

Unary ufuncs

Binary ufuncs

Mathematical Functions

1 Topics

NumPy Math Functions

10 Sub-topics

Trigonometric Functions - sin, cos, tan

Inverse Trigonometric Functions

Hyperbolic Functions

Rounding Functions - round, floor, ceil

Exponential and Logarithmic Functions

Absolute and Sign Functions

Minimum and Maximum Functions

Sum and Product Functions

Cumulative Sum and Product

Difference Function

Broadcasting

1 Topics

NumPy Broadcasting Mechanism

7 Sub-topics

Understanding Broadcasting Rules

Broadcasting with Scalars

Broadcasting 1D with 2D Arrays

Broadcasting Compatible Dimensions

Broadcasting Incompatible Arrays

Practical Broadcasting Examples

Broadcasting Best Practices

Linear Algebra with NumPy

1 Topics

Matrix Operations and Linear Algebra

10 Sub-topics

Matrix Multiplication - dot and matmul

Inner and Outer Products

Matrix Determinant

Matrix Inverse

Matrix Rank

Eigenvalues and Eigenvectors

Matrix Decomposition - SVD

Solving Linear Systems

Matrix Norms

Matrix Trace

Statistical Operations

1 Topics

Statistical Analysis with NumPy

8 Sub-topics

Mean, Median, and Mode

Standard Deviation and Variance

Percentiles and Quantiles

Correlation Coefficient

Covariance

Histogram Functions

Statistical Aggregations with Axis

Weighted Averages

Random Number Generation

1 Topics

Random Numbers and Distributions

10 Sub-topics

Understanding Random Seed

Random Integer Generation

Random Float Generation

Random Choice and Sampling

Random Permutations and Shuffling

Normal Distribution

Uniform Distribution

Binomial and Poisson Distributions

Custom Distribution Sampling

Random Generator Object (new API)

Advanced Indexing Part 1

1 Topics

Boolean and Integer Indexing

6 Sub-topics

Boolean Indexing Basics

Boolean Masks with Conditions

Multiple Boolean Conditions

Integer Array Indexing

Fancy Indexing with 1D Arrays

Fancy Indexing with 2D Arrays

Advanced Indexing Part 2

1 Topics

Advanced Selection Techniques

6 Sub-topics

Using np.where()

Using np.select()

Using np.take() and np.put()

Using np.choose()

Index Arrays and Broadcasting

Advanced Indexing Performance

Sorting and Searching

1 Topics

Sorting and Finding Elements

8 Sub-topics

Sorting Arrays - np.sort()

Sorting Along Axis

Indirect Sorting - np.argsort()

Partial Sorting - np.partition()

Searching Arrays - np.searchsorted()

Finding Unique Elements

Finding Non-zero Elements

Finding Maximum and Minimum Indices

File IO Operations

1 Topics

Saving and Loading Arrays

8 Sub-topics

Saving Arrays - np.save()

Loading Arrays - np.load()

Saving Multiple Arrays - np.savez()

Saving Text Files - np.savetxt()

Loading Text Files - np.loadtxt()

Loading CSV Files - np.genfromtxt()

Handling Missing Data in Files

Binary File Operations

Structured Arrays

1 Topics

Working with Structured Data

7 Sub-topics

Understanding Structured Arrays

Creating Structured Arrays

Accessing Fields

Record Arrays

Nested Structured Arrays

Sorting Structured Arrays

Structured Array Operations

Memory Management and Optimization

1 Topics

Memory and Performance

8 Sub-topics

Understanding Memory Layout

C-contiguous vs F-contiguous

Memory Views and Strides

Copy vs View - Deep Dive

Memory-efficient Operations

Using np.may_share_memory()

Avoiding Unnecessary Copies

Optimizing Large Array Operations

Advanced Operations

1 Topics

Advanced NumPy Techniques

9 Sub-topics

Array Iteration - nditer

Custom Iteration Flags

Vectorization Techniques

Using np.vectorize()

Creating Custom ufuncs

Applying Functions - np.apply_along_axis()

Element-wise Conditionals - np.where() Advanced

Clipping Values - np.clip()

Replacing Values - np.nan_to_num()

Working with NaN and Inf

1 Topics

Handling Special Values

7 Sub-topics

Understanding NaN and Inf

Detecting NaN Values - np.isnan()

Detecting Inf Values - np.isinf()

NaN-aware Aggregations

Removing NaN Values

Filling NaN Values

NaN Propagation Rules

Performance and Best Practices

1 Topics

Optimization and Best Practices

8 Sub-topics

Avoiding Python Loops

Preallocating Arrays

Using In-place Operations

Efficient Array Concatenation

Leveraging Broadcasting

Choosing Appropriate Data Types

Profiling NumPy Code

Common Performance Pitfalls

Practical NumPy Applications

1 Topics

Real-world NumPy Usage

7 Sub-topics

Image Processing Basics

Signal Processing Operations

Time Series Analysis

Numerical Computing

Data Transformation Pipelines

Batch Processing

Scientific Computing Examples

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NumPy Mega Course

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Course Curriculum

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Start Your Journey Today

NumPy Mega Course

Certificate of Completion

Course Curriculum

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