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Python and Data Science from Scratch With RealLife Exercises
Last updated 2/2024
Duration: 22h54m | .MP4 1280x720, 30 fps(r) | AAC, 44100 Hz, 2ch | 5.4 GB
Genre: eLearning | Language: English
Python Data Science with Python programming, NumPy, Pandas, Matplotlib and dive into Data Science with Python Projects
What you'll learn
Learn the skills for collecting, shaping, storing, managing, and analyzing data with Python
The rise of data science needs will create 11.5 million job openings by 2026
Learn In-Demand Data Science Careers
Learn to use Python professionally
Learn to use Python 3
Learn to use Object Oriented Programming
Free software and tools used during the course
You will be able to work with Python functions, namespaces and modules
Apply the Python knowledge you get from this course in coding exercises, real-life scenarios
Build a portfolio with your Python skills
Fundamentals of Pandas Library
Installation of Anaconda and how to use Anaconda
Using Jupyter notebook for Python, python data science
Numpy Arrays for Numpy python
Combining Dataframes, Data Munging and how to deal with Missing Data
How to use Matplotlib library and start to journey in Data Visualization
Whether you're interested in machine learning, data mining, or data analysis, Udemy has a course for you.
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
Python instructors on OAK Academy specialize in everything from software development to data analysis, and are known for their effective.
Python is a multi-paradigm language, which means that it supports many programming approaches. Along with procedural and functional programming styles
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.
Data science requires lifelong learning, so you will never really finish learning.
Python is a popular language that is used across many industries and in many programming disciplines. DevOps engineers use Python to script website.
Python is a general programming language used widely across many industries and platforms. One common use of Python is scripting, which means automating tasks.
Python has a simple syntax that makes it an excellent programming language for a beginner to learn. To learn Python on your own, you first must become familiar
Python is a widely used, general-purpose programming language, but it has some limitations. Because Python is an interpreted, dynamically typed language
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.
Requirements
No prior data science, python, pandas, numpy knowledge is required
Free software and tools used during the python data science course
Basic computer knowledge for python, python data science, python pandas, numpy pandas
Desire to learn data science
Motivation to learn the second largest number of job postings relative python program language among all others
Curiosity for python programming
Desire to learn Python
Desire to work on data science Project
Desire to learn python data science, data science from scratch
Desire to learn python, pandas, numpy, numpy python
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
Description
Welcome to my "
Python and Data Science from Scratch With Real Life Exercises
" course.
Python Data Science with Python programming, NumPy, Pandas, Matplotlib and dive into Data Science with Python Projects
Numpy, Pandas, Data science, data science from scratch, python, pandas, python data science, NumPy, python programming, python and data science from scratch with real life exercises, python for data science, data science python, matplotlib
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, 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. 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.
Do you know data science needs will create
11.5 million job openings by 2026
?
Do you know the average salary is
$100.000
for
data science careers!
DATA SCIENCE CAREERS ARE SHAPING THE FUTURE
Data science experts are needed in almost every field, from government security to dating apps. Millions of businesses and government departments rely on big data to succeed and better serve their customers. So data science careers are in high demand.
If you want to learn one of the employer's most request skills?
If you are curious about Data Science and looking to start your self-learning journey into the world of data with Python?
If you are an experienced developer and looking for a landing in Data Science!
In all cases, you are at the right place!
We've designed for you
"Python and Data Science from Scratch With Real Life Exercises!
" a straight-forward course for the Python programming language
.
In the course, you will have a down-to-earth way explanations with
hands-on projects
. With this course, you will learn Python Programming step-by-step. I made Python 3 programming simple and easy with exercises, challenges, and lots of real-life examples.
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 visualization
s, 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.
This Python and Data Science course is for everyone!
My
"Python and Data Science from Scratch With Real Life Exercises!"
is for everyone! If you don't have any
previous experience,
not a problem
!
This course is expertly designed to teach everyone from complete beginners, right through to professionals ( as a refresher).
Why Python?
Python is a general-purpose, high-level and multi-purpose programming language. The best thing about the Python is, it supports a lot of today's technology including vast libraries for twitter, data mining, scientific calculations, designing, back-end server for websites, engineering simulations, artificial learning, augmented reality and what not! Also, it supports all kinds of App development.
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.
What are the most popular coding languages for data science?
Python for data science
is the most popular programming language for data science. It is a universal language that has a lot of libraries available. It is also a good beginner language. R is also popular; however, it is more complex and designed for statistical analysis. It might be a good choice if you want to specialize in statistical analysis. You will want to know either Python or R and SQL. SQL is a query language designed for relational databases. Data scientists deal with large amounts of data, and they store a lot of that data in relational databases. Those are the three most-used programming languages. Other languages such as Java, C++, JavaScript, and Scala are also used, albeit less so. If you already have a background in those languages, you can explore the tools available in those languages. However, if you already know another programming language, you will likely be able to pick up.
How long does it take to become a data scientist?
This answer, of course, varies. The more time you devote to learning new skills, the faster you will learn. It will also depend on your starting place. If you already have a strong base in mathematics and statistics, you will have less to learn. If you have no background in statistics or advanced mathematics, you can still become a data scientist; it will just take a bit longer. Data science requires lifelong learning, so you will never really finish learning. A better question might be, "How can I gauge whether I know enough to become a data scientist?" Challenge yourself to complete
data science projects
using open data. The more you practice, the more you will learn, and the more confident you will become. Once you have several projects that you can point to as good examples of your skillset as a data scientist, you are ready to enter the field.
How can ı learn data science on my own?
It is possible to learn
data science projects
on your own, as long as you stay focused and motivated. Luckily, there are a lot of online courses and boot camps available. Start by determining what interests you about data science. If you gravitate to visualizations, begin learning about them. Starting with something that excites you will motivate you to take that first step. If you are not sure where you want to start, try starting with learning Python. It is an excellent introduction to programming languages and will be useful as a data scientist. Begin by working through tutorials or Udemy courses on the topic of your choice. Once you have developed a base in the skills that interest you, it can help to talk with someone in the field. Find out what skills employers are looking for and continue to learn those skills. When learning on your own, setting practical learning goals can keep you motivated.
Does data science require coding?
The jury is still out on this one. Some people believe that it is possible to become a data scientist without knowing how to code, but others disagree. A lot of algorithms have been developed and optimized in the field. You could argue that it is more important to understand how to use the algorithms than how to code them yourself. As the field grows, more platforms are available that automate much of the process. However, as it stands now, employers are primarily looking for people who can code, and you need basic programming skills. The
data scientist
role is continuing to evolve, so that might not be true in the future. The best advice would be to find the path that fits your skill set.
What skills should a data scientist know?
A data scientist requires many skills. They need a strong understanding of statistical analysis and mathematics, which are essential pillars of data science. A good understanding of these concepts will help you understand the basic premises of data science. Familiarity with machine learning is also important. Machine learning is a valuable tool to find patterns in large data sets. To manage large data sets, data scientists must be familiar with databases. Structured query language (SQL) is a must-have skill for data scientists. However, nonrelational databases (NoSQL) are growing in popularity, so a greater understanding of database structures is beneficial. The dominant programming language in Data Science is Python - although R is also popular. A basis in at least one of these languages is a good starting point. Finally, to communicate findings.
Is data science a good career?
The demand for data scientists is growing. We do not just have data scientists; we have data engineers, data administrators, and analytics managers. The jobs also generally pay well. This might make you wonder if it would be a promising career for you. A better understanding of the type of work a data scientist does can help you understand if it might be the path for you. First and foremost, you must think analytically.
Data science from scratch
is about gaining a more in-depth understanding of info through data. Do you fact-check information and enjoy diving into the statistics? Although the actual work may be quite technical, the findings still need to be communicated. Can you explain complex findings to someone who does not have a technical background? Many data scientists work in cross-functional teams and must share their results with people with very different backgrounds.
What is python?
Machine learning python
is a general-purpose, object-oriented, high-level programming language. Whether you work in artificial intelligence or finance or are pursuing a career in web development or data science,
Python bootcamp
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 on the premise that there should be only one way (and preferably, one obvious way) to do things, a philosophy that result
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