
Python for Data Science: Learn Data Science From Scratch
Data Science with Python, NumPy, Pandas, Matplotlib, Data Visualization Learn with Data Science project & Python project
Oak Academy
Summary
- Reed courses certificate of completion - Free
Add to basket or enquire
Overview
Hello there,
Welcome to my "Python for Data Science: Learn Data Science From Scratch" course.
Data science, data science Project, data science projects, data science from scratch, data science using python, python for data science, python data science, Numpy, pandas, matplotlib
Data Science with Python, NumPy, Pandas, Matplotlib, Data Visualization Learn with Data Science project & Python project
OAK Academy 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, has a course for you. data literacy, python, data science python, pandas Project, python data science projects, data, data science with Project, pandas projects, pandas, data science with python, numpy
Data science is everywhere. Better data science practices are allowing corporations to cut unnecessary costs, automate computing, and analyze markets. Essentially, data science is the key to getting ahead in a competitive global climate.
Python instructors on OAK Academy specialize in everything from software development to data analysis, and are known for their effective, friendly instruction for students of all levels.
Whether you work in machine learning or finance, or are pursuing a career in web development or data science, Python is one of the most important skills you can learn. Python's simple syntax is especially suited for desktop, web, and business applications. Python's design philosophy emphasizes readability and usability. Python was developed upon the premise that there should be only one way (and preferably one obvious way) to do things, a philosophy that has resulted in a strict level of code standardization. The core programming language is quite small and the standard library is also large. In fact, Python's large library is one of its greatest benefits, providing a variety of different tools for programmers suited for many different tasks.
Ready for the Data Science career?
-
Are you curious about Data Science and looking to start your self-learning journey into the world of data with Python?
-
Are you an experienced developer looking for a landing in Data Science!
In both cases, you are at the right place!
Welcome to Python for Data Science: Learn Data Science From Scratch course
Python is the most popular programming language for the data science process in recent years and also do not forget that data scientist has been ranked the number one job on several job search sites! With Python skills, you will encounter many businesses that use Python and its libraries for data science. Almost all companies working on machine learning and data science use Python’s Pandas library.
In this course you will learn;
-
How to use Anaconda and Jupyter notebook,
-
Fundamentals of Python such as
-
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
-
How to do indexing and slicing on Arrays
-
Lots of stuff about Pandas for data manipulation such as
-
Pandas series and their features
-
Dataframes and their features
-
Hierarchical indexing concept and theory
-
Groupby operations
-
The logic of Data Munging
-
How to deal effectively with missing data effectively
-
Combining the Data Frames
-
How to work with Dataset files
-
And also you will learn fundamentals thing about Matplotlib library such as
-
Pyplot, Pylab and Matplotlib concepts
-
What Figure, Subplot and Axes are
-
How to do figure and plot customization
-
Data science project
-
Python Projects
-
Pandas projects
-
Python data science Projects
-
Data literacy
-
Full stack data science
And we will do many exercises. Finally, we will also have 4 different final projects covering all of these subjects.
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, Pandas or Data Science.
You'll also get:
-
Lifetime Access to The Course
-
Fast & Friendly Support in the Q&A section
Dive in now Python for Data Science: Learn Data Science From Scratch course
We offer full support, answering any questions.
See you in the Python for Data Science: Learn Data Science From Scratch course!
Certificates
Reed courses certificate of completion
Digital certificate - Included
Will be downloadable when all lectures have been completed
Curriculum
-
Course Intro 01:01
-
Data Science: Python is Easy To Learn, Data science Project 10:52
-
Data Science: Setting Up Python for Mac and Windows 17:48
-
Fundamentals of Python 1:42:21
-
Python For Data Science: Data Science 09:49
-
Using Numpy for Data Manipulation 51:09
-
Pandas: Using Pandas for Data Manipulation 6:47:21
-
(Optional) Recap, Exercises, and Bonus Info from the Pandas Library 3:15:51
-
Python For Data Science: Data Visualization 57:53
-
Data Science: Hands-On Projects 2:03:14
Course media
Description
Hello there,
Welcome to my "Python for Data Science: Learn Data Science From Scratch" course.
Data science, data science Project, data science projects, data science from scratch, data science using python, python for data science, python data science, Numpy, pandas, matplotlib
Data Science with Python, NumPy, Pandas, Matplotlib, Data Visualization Learn with Data Science project & Python project
OAK Academy 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, has a course for you. data literacy, python, data science python, pandas Project, python data science projects, data, data science with Project, pandas projects, pandas, data science with python, numpy
Data science is everywhere. Better data science practices are allowing corporations to cut unnecessary costs, automate computing, and analyze markets. Essentially, data science is the key to getting ahead in a competitive global climate.
Python instructors on OAK Academy specialize in everything from software development to data analysis, and are known for their effective, friendly instruction for students of all levels.
Whether you work in machine learning or finance, or are pursuing a career in web development or data science, Python is one of the most important skills you can learn. Python's simple syntax is especially suited for desktop, web, and business applications. Python's design philosophy emphasizes readability and usability. Python was developed upon the premise that there should be only one way (and preferably one obvious way) to do things, a philosophy that has resulted in a strict level of code standardization. The core programming language is quite small and the standard library is also large. In fact, Python's large library is one of its greatest benefits, providing a variety of different tools for programmers suited for many different tasks.
Ready for the Data Science career?
-
Are you curious about Data Science and looking to start your self-learning journey into the world of data with Python?
-
Are you an experienced developer looking for a landing in Data Science!
In both cases, you are at the right place!
Welcome to Python for Data Science: Learn Data Science From Scratch course
Python is the most popular programming language for the data science process in recent years and also do not forget that data scientist has been ranked the number one job on several job search sites! With Python skills, you will encounter many businesses that use Python and its libraries for data science. Almost all companies working on machine learning and data science use Python’s Pandas library. Thanks to the large libraries provided, 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 Pandas library will be the right choice for you to take part in this world and create your own opportunities,
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 libraries such as Numpy, Pandas, and Matplotlib step by step.
Throughout the course, we will teach you how to use the Python to analyze data, create beautiful visualizations, and use powerful machine learning algorithms and we will also do a variety of exercises to reinforce what we have learned in this Python for Data Science course.
In this course you will learn;
-
How to use Anaconda and Jupyter notebook,
-
Fundamentals of Python such as
-
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
-
How to do indexing and slicing on Arrays
-
Lots of stuff about Pandas for data manipulation such as
-
Pandas series and their features
-
Dataframes and their features
-
Hierarchical indexing concept and theory
-
Groupby operations
-
The logic of Data Munging
-
How to deal effectively with missing data effectively
-
Combining the Data Frames
-
How to work with Dataset files
-
And also you will learn fundamentals thing about Matplotlib library such as
-
Pyplot, Pylab and Matplotlib concepts
-
What Figure, Subplot and Axes are
-
How to do figure and plot customization
-
Data science project
-
Python Projects
-
Pandas projects
-
Python data science Projects
-
Data literacy
-
Full stack data science
And we will do many exercises. Finally, we will also have 4 different final projects covering all of these subjects.
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, Pandas or Data Science.
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 does no problem, you will learn anything 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.
What is data science?
We have more data than ever before. But data alone cannot tell us much about the world around us. We need to interpret the information and discover hidden patterns. This is where data science comes in. Data science python uses algorithms to understand raw data. The main difference between data science and traditional data analysis is its focus on prediction. Python data science seeks to find patterns in data and use those patterns to predict future data. It draws on machine learning to process large amounts of data, discover patterns, and predict trends. Data science using python includes preparing, analyzing, and processing data. It draws from many scientific fields, and as a python for data science, it progresses by creating new algorithms to analyze data and validate current methods.
What does a data scientist do?
Data Scientists use machine learning to discover hidden patterns in large amounts of raw data to shed light on real problems. This requires several steps. First, they must identify a suitable problem. Next, they determine what data are needed to solve such a situation and figure out how to get the data. Once they obtain the data, they need to clean the data. The data may not be formatted correctly, it might have additional unnecessary data, it might be missing entries, or some data might be incorrect. Data Scientists must, therefore, make sure the data is clean before they analyze the data. To analyze the data, they use machine learning techniques to build models. Once they create a model, they test, refine, and finally put it into production.
You'll also get:
-
Lifetime Access to The Course
-
Fast & Friendly Support in the Q&A section
Dive in now Python for Data Science: Learn Data Science From Scratch course
We offer full support, answering any questions.
See you in the Python for Data Science: Learn Data Science From Scratch course!
Who is this course for?
- Anyone who wants to learn data science,
- Anyone who plans a career in data scientist,
- Software developer whom want to learn python data science,
- Anyone eager to learn Data Science python with no coding background
- Anyone eager to learn Python with no coding background
- Anyone who wants to learn Pandas
- Anyone who wants to learn Numpy
- Anyone who wants to learn Matplotlib
- Anyone who wants to work on real data science project
- Anyone who wants to learn data visualization projects.
- people who want to learn python projects, data science projects
Requirements
- No prior data science, python knowledge is required
- Free software and tools used during the python data science course
- Basic computer knowledge
- Desire to learn data science
- Curiosity for python programming
- Desire to learn Python
- Desire to work on data science Project
- Desire to learn python with numpy, pandas, matplotlib
- Desire to learn python data science with python, numpy, pandas, matplotlib
- LIFETIME ACCESS, course updates, new content, anytime, anywhere, on any device
- Nothing else! It’s just you, your computer and your ambition to get started today
Questions and answers
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Legal information
This course is advertised on Reed.co.uk by the Course Provider, whose terms and conditions apply. Purchases are made directly from the Course Provider, and as such, content and materials are supplied by the Course Provider directly. Reed is acting as agent and not reseller in relation to this course. Reed's only responsibility is to facilitate your payment for the course. It is your responsibility to review and agree to the Course Provider's terms and conditions and satisfy yourself as to the suitability of the course you intend to purchase. Reed will not have any responsibility for the content of the course and/or associated materials.