Genre: eLearning | MP4 | Video: h264, 1280x720 | Audio: aac, 48000 Hz
Language: English | VTT | Size: 6.37 GB | Duration: 10 section | 90 lectures | (6h 14m)
What you'll learn
Collect data, clean data, combine data, enrich data, model data, and visualize data. The full Data Science process.
How to make simple and efficient Data Analysis
Master the Pandas data structures Series and DataFrames
Use the libraries of Pandas and know how to explore it further
Master the NumPy Array and understand the strength of it
Understand the difference between NumPy and Pandas
Master the built in Data Structures in Python and understand their strengths
Built projects from external sources like CSV files
Combine datasets to enrich the value of Data Science projects
Master vectorizations and understand the power of it
Very basic Python skills - understand integers, floats, strings, for-loop
Simple math operations and basic percentage knowledge
Starting Data Science with NumPy and Pandas in Python can be overwhelming.
Data structures with endless functionality.
Large and complex libraries.
...and at first, difficult syntax to understand.
Wrong approach to learning
Most tutorials and courses are focused on covering the broad basis of Pandas, NumPy, or Python data strctures.
Too much focus on covering all the all awesome functionalities and syntax.
No real examples or too tailored to be used in real life.
Not enough coding included to really understand it.
This course learning approach
Master a small basis to get full power with Python built-in data structures, NumPy, and Pandas to make real Data Science project.
Work on real life examples with real datasets.
Make real projects in Python built-in data structures, NumPy arrays, and Pandas Series and DataFrames to understand to true power of each.
Keep incremental learning cycles small to ensure you master each step.
All datasets and source code available in the course and you will do all the coding along.
Approach with Python
The simple coding exercises will be done in the Udemy platform.
More advanced will be done in your own environment.
You can use PyCharm (the best Integrated Development Environment (IDE) for Python and it is FREE) or another strong IDE. You can also use Jupyter Notebook.
What will we cover in this course?
Python built-in data structures with real life examples.
Learn the power of Python lists.
How read CSV files with datasets and explore the datasets, done on real life dataset.
Understand and use Python dictionaries to master the power of them.
Master the NumPy array to understand the power and limitations compared to Python lists and dictionaries.
Understand and master the power of vectorization with NumPy.
Work like a Data Scientist with NumPy: Load the data, understand the data, clean the data, enrich the data, explore the data, visualize the data.
Making real project with NumPy on real life large datasets.
Creating Descriptions and fitting lines to data points.
Pandas compared to NumPy. When to use what?
Understand the data structures of Pandas: Series and DataFrames.
Master the power of vectorization with Pandas.
Use Pandas on large real life datasets.
How to combine (merge and join) datasets from different sources.
Dealing with missing data points.
Convert data to the datatype needed and dealing with errors.
Visualize data on world maps.
Calculate new data.
Test hypothesis of data from real sources.
How to continue your journey as a Data Scientiest.
You code along - you only learn by trying yourself - 50+ coding exercises
At each step you make the implementation along with me.
You implement it on all stages to increase your understanding of security
Basically, we learn along the way with more than 50+ coding exercises.
What is needed to fully understand this course?
You have basic understand of Python.
Understand basic math from elementary school level.
Who is this course for?
You want to learn and understand the Data Science process.
Want to master NumPy and Pandas like a professional.
Those who want to try it with programming examples to fully understand the depth of each lesson
The course has a 30 day money back guarantee that ensures if you are not satisfied, you will get your money back. Also, feel free to contact me directly if you have any questions.
Who this course is for:
Students that want to get started using Pandas and NumPy data structures
Students that start their Data Science journey and need the foundation
Curious Data Science student that want to have a programmatic approach to Data Science
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