With 165 lectures and 25 hours of videos this comprehensive course teaches how to use Python to analyze data, create beautiful visualizations, and use powerful machine learning algorithms. The course is provided by Jose Portilla (Pierian Data Inc.).
The class taught me the following:
- programming with Python and data analysis:
- NumPy for numerical data
- SciPy for scientific and mathematical problems
- Pandas Dataframes for data analysis to solve complex tasks, and to handle Excel Files
- Web scraping with python
- connect Python to SQL
- data visualization:
- Matplotlib for Python plotting
- Seaborn for statistical plots
- Plotly for interactive dynamic visualizations
- Choropleth maps for geographical plotting
- machine learning algorithms with SciKit-learn:
- Linear Regression
- K Nearest Neighbors
- K Means Clustering
- Random Forest and Decision Trees
- Natural Language Processing and spam filters
- Support Vector Machines
- Deep Learning:
- Neural Networks with TensorFlow
- Big Data analysis:
- Spark and RDD
Credentials: