Bestseller हिन्दी में

NumPy Course for Advanced

Master advanced NumPy for elite data science and AI careers!

4.6

Advance

Certificate of Completion

Complete this course and earn a verified certificate to showcase your achievement.

Verified & ShareableShare on LinkedIn, resume, or portfolio

QR Code VerificationEmployers can instantly verify online

Unique Certificate IDTamper-proof with unique serial number

Industry RecognisedAccepted by 500+ companies across India

This is to certify that

Your Name Here

has successfully completed

NumPy Course for Advanced

4 Modules

Course Curriculum

4 Modules · 13 Chapters · 13 Topics · 98 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

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

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)

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()

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

0.0

Course Rating

No reviews yet. Be the first to review this course!

Frequently Asked Questions

No FAQs for this course yet.

Preview this course

₹4,499 ₹6,749 33% OFF

Lifetime access to all materials

Certificate of completion

Available in multiple languages

Access on mobile & desktop

7-Day Money-Back Guarantee Not satisfied? Get a full refund within 7 days, no questions asked. Zero risk.

NumPy Course for Advanced

Certificate of Completion

Course Curriculum

Student Reviews

Frequently Asked Questions

Start Your Journey Today

NumPy Course for Advanced

Certificate of Completion

Course Curriculum

Student Reviews

Frequently Asked Questions

Related Courses

NumPy Memory Optimization

Pandas Data Wrangling Essentials

Matplotlib Complete Professional Bootcamp

Start Your Journey Today