Course Details
Hello there,
Ready for the Data Science career?
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 Matplotlb concepts
-
What Figure, Subplot and Axes are
-
How to do figure and plot customization
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.
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 Python for Data Science: Learn Data Science From Scratch course
We offer full support, answering any questions.
See you in the course!
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
What you will learn
- Fundamentals of Pandas Library (Data science, Python data science, data science project, python project)
- Learn Fundamentals of Python for effectively using Data Science
- Installation of Anaconda and how to use for Python, Pandas, Numpy
- Using Jupyter notebook
- Numpy arrays
- Series and Features in Python for Data science, numpy and pandas
- Combining Dataframes, Data Munging and how to deal with Missing Data
- How to use Matplotlib library and start to journey in Data Visualization
- Also, why you should learn Python and Pandas Library (numpy, pandas, python numpy pandas)
- Learn Data Science with Python, Numpy and pandas
- 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.
Who should attend
- 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
TAKE THIS COURSE
1304 Students
