Data-Science-classes-with-Python-at-cbitss.pptx
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The document outlines a comprehensive training program in data science using Python, highlighting its importance across various industries such as healthcare and finance. It details the data science workflow, which includes data collection, cleaning, exploratory data analysis, and machine learning applications with Python libraries like NumPy, Pandas, and Scikit-learn. Practical applications of data science are also discussed, including predictive analytics and natural language processing.
Data-Science-classes-with-Python-at-cbitss.pptx
- 1. Data Science with Python A Comprehensive Training Program
- 2. Introduction to Data Science Data Science Defined The art of extracting knowledge from data Impact Across Industries Healthcare, finance, retail, and more
- 3. Why Python for Data Science? Simple to Learn Beginner-friendly syntax Powerful Libraries NumPy, Pandas, Matplotlib, Scikit-learn Active Community Support and resources available
- 4. Data Science Workflow 1 Data Collection Gathering raw data 2 Data Cleaning & Preprocessing Preparing data for analysis 3 EDA & Model Building Understanding patterns and building models 4 Evaluation & Deployment Testing and implementing solutions
- 5. Python Libraries for Data Science NumPy Numerical computing Pandas Data manipulation Matplotlib & Seaborn Data visualization Scikit-learn Machine learning
- 6. Data Preprocessing with Python Missing Values Handling missing data points Data Transformation Scaling, normalization, and encoding Feature Scaling Standardizing feature values
- 7. Exploratory Data Analysis (EDA) Summary Statistics Mean, median, standard deviation Data Visualization Bar charts, histograms, scatter plots Pattern Recognition Identifying trends and insights
- 8. Machine Learning with Python 1 Supervised Learning Regression & classification 2 Model Training Fitting models to data 3 Model Evaluation Measuring performance 4 Hyperparameter Tuning Optimizing model parameters
- 9. Real-World Applications 1 Predictive Analytics Stock market forecasting, sales prediction 2 Natural Language Processing Chatbots, sentiment analysis 3 Computer Vision Image recognition, medical diagnosis