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Learn Numpy and get comfortable with Python Numpy in order to start into Data Science and Machine Learning.

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- Curriculum
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- Reviews

Hello there,

Welcome to **Python Numpy: Machine Learning & Data Science Course**

Are you ready for the

**Data Science**career?

Do you want to learn the Python Numpy from Scratch? or

Are you an experienced Data scientist and looking to improve your skills with Numpy!

In both cases, you are at the right place! The number of companies and enterprises using Python is increasing day by day. The world we are in is experiencing the age of informatics. Python and its **Numpy library **will be the right choice for you** **to take part in this world and create your own opportunities,

**Numpy** is a library for the **Python** programming language, adding support for large, multi-dimensional arrays and matrices, along with a large collection of high-level mathematical functions to operate on these arrays. Moreover, **Numpy** forms the foundation of the **Machine Learning** stack.

**NumPy** aims to provide an array object that is up to 50x faster than traditional Python lists. The array object in **NumPy** is called ndarray , it provides a lot of supporting functions that make working with ndarray very easy. Arrays are very frequently **used** in data science, where speed and resources are very important.

In this course, we will open the door of the **Data Science** world and will move deeper. You will learn the fundamentals of **Python** and its beautiful library **Numpy** step by step with hands-on examples. Most importantly in Data Science, you should know how to use effectively the Numpy library. Because this library is limitless.

Throughout the course, we will teach you how to **use the Python in Linear Algebra, and Neural Network concept**, and use powerful machine learning algorithms and we will also do a variety of exercises to reinforce what we have learned in this **Machine Learning with NumPy and Python Data Science** course.

**In this course you will learn;**

How to use Anaconda and Jupyter notebook,

Fundamentals of Python

Datatypes in Python,

Lots of datatype operators, methods and how to use them,

Conditional concept, if statements

The logic of Loops and control statements

Functions and how to use them

How to use modules and create your own modules

Data science and Data literacy concepts

Fundamentals of Numpy for Data manipulation such as

Numpy arrays and their features

Numpy functions

Numexpr module

How to do indexing and slicing on Arrays

Linear Algebra

Using numpy in Neural Network

And we will do many exercises. Finally, we will also do a **neural network project with Numpy.**

**Why would you want to take this course?**

We have prepared this course in the simplest way for beginners and have prepared many different exercises to help them understand better.

**No prior knowledge is needed!**

In this course, you need no previous knowledge about Python or Numpy.

**This course will take you from a beginner to a more experienced level.**

If you are new to data science or have no idea about what data science is, no problem, you will learn anything from scratch you need to start data science.

If you are a software developer or familiar with other programming languages and you want to start a new world, you are also in the right place. You will learn step by step with hands-on examples.

**You'll also get:**

· Lifetime Access to The Course

· Fast & Friendly Support in the Q&A section

· Udemy Certificate of Completion Ready for Download

Dive in now **Machine Learning with NumPy and Python Data Science** course

We offer **full support**, answering any questions.

See you in the course!

- No prior knowledge of Numpy is required
- Free software and tools used during the course
- Basic computer knowledge
- Desire to learn Python and Numpy library
- Nothing else! It’s just you, your computer and your ambition to get started today
- Desire to learn data science
- Desire to learn Python
- Desire to work on machine learning
- Desire to learn python machine learning a-z

- Fundamentals of Numpy Library and a little bit more
- Installation of Anaconda and how to use
- Using Jupyter notebook
- Learn Fundamentals of Python for effectively using Numpy Library
- Numpy arrays
- Numpy functions
- Linear Algebra
- Most importantly you will learn the Mathematics beyond the Neural Network
- Also, why you should learn Python and Numpy Library
- The most important aspect of Numpy arrays is that they are optimized for speed. We’re going to do a demo where I prove to you that using a Numpy.
- You will learn how to use the Python in Linear Algebra, and Neural Network concept, and use powerful machine learning algorithms
- OAK offers highly-rated data science courses that will help you learn how to visualize and respond to new data, as well as develop innovative new technologies
- Whether you’re interested in machine learning, data mining, or data analysis, Udemy has a course for you.
- Data science is everywhere. Better data science practices are allowing corporations to cut unnecessary costs, automate computing, and analyze markets.
- Data science is the key to getting ahead in a competitive global climate.
- Data science uses algorithms to understand raw data. The main difference between data science and traditional data analysis is its focus on prediction.
- Data Scientists use machine learning to discover hidden patterns in large amounts of raw data to shed light on real problems.
- Python is the most popular programming language for data science. It is a universal language that has a lot of libraries available.
- Data science requires lifelong learning, so you will never really finish learning.
- It is possible to learn data science on your own, as long as you stay focused and motivated. Luckily, there are a lot of online courses and boot camps available
- Some people believe that it is possible to become a data scientist without knowing how to code, but others disagree.
- A data scientist requires many skills. They need a strong understanding of statistical analysis and mathematics, which are essential pillars of data science.
- The demand for data scientists is growing. We do not just have data scientists; we have data engineers, data administrators, and analytics managers.
- Numpy python
- machine learning data science course
- machine learning python
- Data analysis, numpy python
- Data analysis with pandas and python
- Machine learning a-z

- Anyone who wants to learn Numpy
- Anyone who want to use effectively linear algebra,
- Software developer whom want to learn the Neural Network’s math,
- Data scientist whom want to use effectively Numpy array
- Anyone interested in data sciences
- Anyone who plans a career in data scientist,
- Anyone eager to learn python with no coding background
- Anyone who is particularly interested in big data, machine learning
- Anyone eager to learn Python with no coding background
- Anyone who wants to learn Numpy

- Lecture 1 Python Numpy Course with Machine Learning
- Lecture 2 FAQ regarding Data Science and Machine Learning
- Lecture 3 FAQ regarding Python and Numpy Python

- Lecture 8 Data Types in Python
- Lecture 9 Operators in Python
- Lecture 10 Conditionals in Numpy Python
- Lecture 11 Loops in Numpy Python
- Lecture 12 Lists, Tuples, Dictionaries and Sets in Python
- Lecture 13 Data Type Operators and Methods
- Lecture 14 Modules in Python
- Lecture 15 Functions in Python
- Lecture 16 Exercise Analyse in Python
- Lecture 17 Exercise Solution in Python

- Lecture 18 Logic of OOP
- Lecture 19 Constructor in Object Oriented Programming (OOP)
- Lecture 20 Methods in Object Oriented Programming (OOP)
- Lecture 21 Inheritance in Object Oriented Programming (OOP)
- Lecture 22 Overriding and Overloading in Object Oriented Programming (OOP)
- Lecture 23 Python: Object Oriented Programming (OOP) 1

- Lecture 24 What is Numpy?
- Lecture 25 Why Numpy?
- Lecture 26 Array and Features in Numpy Python
- Lecture 27 Array’s Operators in Numpy Python
- Lecture 28 Numpy Functions in Numpy Python
- Lecture 29 Indexing and Slicing in Numpy Python
- Lecture 30 Numpy Exercises in Numpy Python
- Lecture 31 Using Numpy in Linear Algebra
- Lecture 32 Numpy: 2
- Lecture 33 NumExpr Guide in Numpy Python
- Lecture 34 Using Numpy with Creating Neural Network in Numpy Python
- Lecture 35 Numpy: 3

dive into numpy with this course

A very good course for students who look forward to study Machine Learning as a future career path. The course consists with many different examples for students to understand more difficult concepts with much clearer approach!

This is one of the best courses on Udemy to learn "Machine Learning and Data Science" using Python Numpy. This course course is suitable for both beginners and for professionals.

Thank you OAK Academy.

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