Complete Data Science Training with Python for Data Analysis

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Complete Data Science Training with Python for Data Analysis, Complete Guide to Practical Data Science with Python: Learn Statistics, Visualization, Machine Learning & More

Created by Minerva Singh

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What you'll learn

• Install Anaconda & Work Within The iPytjhon/Jupyter Environment, A Powerful Framework For Data Science Analysis
• Become Proficient In Using The Most Common Python Data Science Packages Including Numpy, Pandas, Scikit & Matplotlib
• Be Able To Read In Data From Different Sources (Including Webpage Data) & Clean The Data
• Carry Out Data Exploratory & Pre-processing Tasks Such As Tabulation, Pivoting & Data Summarizing In Python
• Become Proficient In Working With Real Life Data Collected From Different Sources
• Carry Out Data Visualization & Understand Which Techniques To Apply When
• Carry Out The Most Common Statistical Data Analysis Techniques In Python Including T-Tests & Linear Regression
• Understand The Difference Between Machine Learning & Statistical Data Analysis
• Implement Different Unsupervised Learning Techniques On Real Life Data
• Implement Supervised Learning (Both In The Form Of Classification & Regression) Techniques On Real Data
• Evaluate The Accuracy & Generality Of Machine Learning Models
• Build Basic Neural Networks & Deep Learning Algorithms
• Use The Powerful H2o Framework For Implementing Deep Neural Networks

Requirements

• Be Able To Use PC At A Beginner Level, Including Being Able To Install Programs
• A Desire To Learn Data Science
• Prior Knowledge Of Python Will Be Useful But NOT Necessary