| Course Name | Duration | Classes | Total Fee | Mode of Training | Class Timing |
|---|---|---|---|---|---|
|
Numpy
Course |
2 Months |
40 |
60,000 PKR |
Online & Face-to-Face |
To be decided mutually with students |
Numpy Training Certification Course
In addition to validating your technical skills, Numpy Certification can help you advance your expertise. Once Numpy Certified, you’ll be eligible for perks that help you show off your achievements and keep learning. Register for exams and claim benefits at Technocation training.
Technocation provides an excellent faculty and qualified developers as there is a remarkable prospect in this field. One can make his/her Career with the help of both Numpy Training and establish an identity and get guidance in Rawalpindi.
Therefore, we aim to shape inspiring students with in-depth training to meet the requirements of the IT industry and build substantial grounds in Numpy Training by exhibiting students with various projects. Technocation also bestows the Best Numpy Training Course in Rawalpindi, Islamabad.
We guide people from every background to change their lives via our career-oriented short-term courses in Rawalpindi. Our evening and online course primarily focus on school, college, university students, and full/part-time employees.
Advantages of Learning Numpy
- Efficient Computations: NumPy is optimized for fast numerical operations on large datasets.
- Array Manipulation: Provides powerful tools for handling multi-dimensional arrays.
- Mathematical Functions: Supports complex mathematical and statistical operations.
- Broadcasting: Enables operations on arrays of different shapes without explicit looping.
- Integration: Works seamlessly with libraries like pandas, matplotlib, and scikit-learn.
- Memory Efficient: Uses less memory compared to standard Python lists.
- Data Preprocessing: Essential for cleaning and preparing data for machine learning.
- Community Support: Has extensive documentation and a large user base.
- Cross-Platform: Compatible across operating systems and Python versions.
- Foundational: Builds the groundwork for deeper data science and AI skills.
Numpy Training Certification Course Outline
This advanced course focuses on mastering complex data manipulation, numerical computations, and efficient use of Numpy for scientific and machine learning applications. Participants will explore advanced concepts such as broadcasting, vectorization, memory optimization, and parallel processing.
Module 1:Numpy Fundamentals & Arrays
- Recap of Numpy Basics: Arrays, Indexing, Slicing, and Shapes
- Data Types and Structured Arrays
- Creating Arrays from Various Sources (Lists, Tuples, etc.)
- Practical Exercises: Array manipulations, Reshaping, Transposing
Module 2:Advanced Indexing and Slicing
- Boolean Indexing
- Fancy Indexing and Advanced Slicing Techniques
- Multi-dimensional Indexing and Subarrays
- Exercises: Masking, Advanced Filtering, and Conditional Slicing
Module 3:Broadcasting and Vectorization
- Basics of Numpy Broadcasting
- Vectorized Operations vs. Loops
- Performance Optimization with Numpy
- Hands-on: Matrix Operations, Element-wise Functions
Module 4:Mathematical Operations and Statistical Functions
- Aggregations: Mean, Median, Variance, and Standard Deviation
- Linear Algebra Operations: Dot Product, Eigenvalues, Matrix Decomposition
- Random Sampling and Statistical Analysis
- Exercises: Covariance matrices, Hypothesis Testing
Module 5:Handling Large Data with Numpy
- Memory Efficient Array Manipulation
- Numpy’s memmap for Large Array Storage
- Performance Tuning Techniques (Profiling and Optimization)
- Practical Case Study: Processing Big Data Sets
Module 6: Advanced Interoperability
- Integrating Numpy with Pandas, Matplotlib, Scipy
- Serialization of Numpy Arrays (.npy, .npz)
- Parallel Computing with Numpy and numba
- Exercises: Parallel Operations & Performance Comparisons
Module 7:Machine Learning with Numpy
- Fundamentals of Numpy in Machine Learning Pipelines
- Matrix Manipulations for Neural Networks
- Advanced Gradient Descent Techniques
- Hands-on: Building a Simple ML Model using Numpy and Scikit-learn
Module 8:Advanced Topics & Projects
- Numpy Advanced Operations: Broadcasting Tricks, Low-level Array Manipulation
- Real-World Projects: Complex Scientific Simulations & Data Analysis
- Project Presentation and Optimization Discussion
- Final Hands-on Exercise: Building an End-to-End Pipeline with Numpy
Module 9: Introduction to NumPy
- What is NumPy?
- Installing NumPy
- Basic Features
- Creating Arrays
- Array Attributes
- Indexing and Slicing
- Arithmetic Operations
- Broadcasting
- Universal Functions
Experience and Inspiring Trainers:
Our trainers bring their years of industry experience during the course. They are expert and passionate about delivering inspiring training as they know training inside out. They will advise you on all the options to make sure you get the best possible result.
Real-time Practice and Projects:
- Weekly hands-on exercises
- Mid-term and final projects
- Code reviews and in-class presentations
Prerequisites for Numpy Course:
- Master advanced Numpy techniques for efficient data handling
- Perform complex mathematical and statistical computations
- Optimize performance for large-scale numerical computations
- Integrate Numpy into data science and machine learning workflows
Basic understanding of Python and fundamental Numpy concepts.
Certificate:
Finally completing this training you will receive a course completion certificate along with internship in Numpy Training so you can get recognition for your new skills.
Course Material:
Softy Copy notes are briefly included in this course
Support and Careers Advice:
In the end our trainers are always ready to help you for any problems or question regarding Numpy. We prepare students for facing Interview questions on Numpy and help them to build their online resume. Our more than 90% students are placed in good MNCs.
“Our Student Success is Our Mission”.