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Data Science and Machine Learning with Python – Intermediate Hands-On Coding
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4 hours 3 minutes 
english
Online - Self Paced
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About Data Science and Machine Learning with Python – Intermediate Hands-On Coding
Introduction to Data Science with Python
Class Project
What is Data Science?
Tool Overview
How To Find Help
| Data Loading |
Loading Excel and CSV files
Loading Data from SQL
Loading Any Data File
Dealing with Huge Data
Combining Multiple Data Sources
| Data Cleaning |
Dealing with Missing Data
Scaling and Binning Numerical Data
Validating Data with Schemas
Encoding Categorical Data
| Exploratory Data Analysis |
Visual Data Exploration
Descriptive Statistics
Dividing Data into Subsets
Finding and Understanding Relations in the Data
| Machine Learning |
Linear Regression for Price Prediction
Decision Trees and Random Forests
Machine Learning Classification
Data Clustering for Deeper Insights
Validation of Machine Learning Models
Machine Learning Interpretability
Intro to Machine Learning Fairness
| Visuals & Reports |
Visualization Basics
52 Geospatial new
Exporting Data and Visualizations
Creating Presentations directly in Jupyter
Generating PDF Reports from Jupyter
Conclusion and Congratulations!
What You Will Learn?
- Are you ready to learn the skills that are in high demand across all industries? .
- Machine Learning and data science are essential for making informed decisions in today's business world. And the best way to learn these skills is through the power of Python..
- Follow the free code resource book on: Data-Science-Gui.de (no e-mail).
- Python is the go-to language for data science, and in this course, we will dive deep into its capabilities. This class is designed for both beginners and intermediate students, so don't worry if you're new to programming. This class assumes some Python knowledge, but if you'd prefer a high-level introduction without programming application to data science, I have another class: The No-Code Data Science Master Class..
- We will start by covering the basics of Python syntax and then move on to the full data science workflow, including:.
- We will be using popular and freely available Python libraries such as Jupyter, NumPy, SciPy, Pandas, MatPlotLib, Seaborn, and Scikit-Learn..
- By the end of this class, you will not only have a solid understanding of data science and analytics but also be able to quickly learn new libraries and tools. So, don't wait any longer and enroll in this Python Data Science Master Class today!.
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- Who am I?.
- Jesper Dramsch is a machine learning researcher working between physical data and deep learning..
- I am trained as a geophysicist and shifted into Python programming, data science and machine learning research during work towards a PhD. During that time I created educational notebooks on the machine learning contest website Kaggle (part of Alphabet/Google) and reached rank 81 worldwide. My top notebook has been viewed over 64,000 times at this point. Additionally, I have taught Python, machine learning and data science across the world in companies including Shell, the UK government, universities and several mid-sized companies. As a little pick-me-up in 2020, I have finished the IBM Data Science certification in under 48h..
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- Other Useful Links:.
- My website & blog - https://dramsch.netThe weekly newsletter - https://dramsch.net.
- ewsletter.
- Twitter - https://twitter.com/jesperdramschLinkedin - https://linkedin.com/in/mlds.
- Youtube - https://www.dramsch.net/youtubeCamera gear - https://www.dramsch.net/r/gear.