Python for Data Science and Machine Learning Bootcamp

Course Overview

• Course Title: Python for Data Science and Machine Learning Bootcamp
• Instructor: Jose Portilla
• Target Audience:
  • Beginners with some programming experience
  • Experienced developers looking to transition to Data Science
• Prerequisites:
  • Some programming experience
  • Admin permissions to download files

Curriculum Highlights

• Key Topics Covered:
  • Programming with Python
  • NumPy with Python
  • Using pandas Data Frames
  • Handling Excel Files with pandas
  • Web scraping with Python
  • Connecting Python to SQL
  • Data visualizations with matplotlib and seaborn
  • Interactive visualizations with Plotly
  • Machine Learning with SciKit Learn
    • Linear Regression
    • K Nearest Neighbors
    • K Means Clustering
    • Decision Trees
    • Random Forests
    • Natural Language Processing
    • Neural Nets and Deep Learning
    • Support Vector Machines
• Key Skills Learned:
  • Use Python for Data Science and Machine Learning
  • Use Spark for Big Data Analysis
  • Implement Machine Learning Algorithms
  • Use NumPy for Numerical Data
  • Use Pandas for Data Analysis
  • Use Matplotlib for Python Plotting
  • Use Seaborn for statistical plots
  • Use Plotly for interactive dynamic visualizations
  • Use SciKit-Learn for Machine Learning Tasks
  • K-Means Clustering
  • Logistic Regression
  • Linear Regression
  • Random Forest and Decision Trees
  • Natural Language Processing and Spam Filters
  • Neural Networks
  • Support Vector Machines

Course Format

• Duration: 25 hours on-demand video
• Format: Self-paced online course
• Resources:
  • 13 articles
  • 5 downloadable resources
  • Access on mobile and TV
  • Certificate of completion