1. Math for Machine Learning
1.1. **Course Project:** Machine Learning Model for Data Overload and Insights
1.1.1. **Milestone 1:** Exploratory Data Analysis (EDA)
1.1.1.1. Pandas: Data Preprocessing
1.1.1.2. Pandas: Descriptive Statistics
1.1.2. **Milestone** **2:** Data Visualization of EDA
1.1.2.1. Matplotlib/Seaborn: Data Visualization Techniques
1.1.3. **Terminal Assessment:** Machine Learning Model Presentation
2. Machine Learning and Predictive Analytics
2.1. **Course Project:** Predictive Analytics and Sales Forecasting
2.1.1. **Milestone 1: ** Project Predictive Model:
2.1.1.1. Pandas/NumPy: Data Preprocessing
2.1.1.2. Pandas/NumPy: Descriptive Statistics
2.1.1.3. Integration of Machine Learning MAlgorithms (Multiple Linear Regression)
2.1.2. **Milestone 2: ** Project Forecasting Model with Visualizations:
2.1.2.1. Time Series Analysis
2.1.2.2. Forecasting Techniques
2.1.2.3. Maplotib/Seaborn: Visualizing Time Series Data and Forecasting Results
2.1.3. **Terminal Assessment: ** Project Presentation:
3. Data Mining Principles
3.1. **Course Project:** Customer Segmentation for Personalized Financial Products
3.1.1. **Milestone 1: ** Project Data Preparation and Exploratory Analysis Report
3.1.2. **Milestone 2: ** Clustering Implementation and Initial Segmentation Report
3.1.3. **Terminal Assessment:** Final Report and Product Recommendations
4. Statistical Analysis
4.1. **Course Project:** Sales
4.1.1. **Milestone 1:** Descriptive Statistics
4.1.1.1. Anomaly Detection
4.1.2. **Milestone 2:** Inferrential Statistics
4.1.2.1. Data Validation
4.1.2.2. Trend and Pattern Identification
4.1.3. **Terminal Assessment: ** Complication of Report
4.2. Financial Analysis
4.3. Mini-Thesis/Business(Statistical Report
4.4. Tool/s: Python
4.4.1. Data Manipulation
4.4.1.1. Pandas
4.4.2. Calculations
4.4.2.1. NumPy
4.4.2.2. SciPy
4.4.3. Visualizations
4.4.3.1. Matplotlib
4.4.3.2. Seaborn
4.5. Tool: JASP
4.6. Topic Outline
4.6.1. Descriptive Statistics
4.6.1.1. Central Tendency
4.6.1.2. Variability/Standard Deviation
4.6.1.3. Skewness
4.6.1.4. Relative Position
4.6.2. Inferential Statistics
4.6.2.1. z-test*
4.6.2.2. t-test
4.6.2.3. ANOVA
4.6.2.4. chi-square*
4.6.2.5. correlational analysis
4.6.2.6. regression analysis