Data Science course details
- Course Duration150 Hrs
- New Batch StartsEvery Monday
- Mode of TrainingClassRoom Online
Course content
- Summary Measures
- Hypothesis Testing
- Crosstabs, Correlations & ANOVA
- Data Types
- Variables
- Strings
- Lists
- Tuples
- Dictionaries
- Sets
- Conditional Statements
- Loops
- Python Comprehension
- Working with Files
- Functions
- Classes
- Pandas
- Numpy
Data Preprocessing
- Data Normalization
- Handling Skew Data
- Handling Missing Data
Feature Engineering
- Variance based filtering
- Correlation based filtering
- Features Creation
- Techniques to create new features
- Feature Selection
- Statistical feature selection
- Model based feature selection
- Feature Extraction & Transformation
Data Visualizationc
- Categorical variables vs Continuous Variables
- Various graphs using Matplotlib, Seaborn
- Linear Regression
- Logistic Regression
- Support Vector Machines
- CART
- CHAID
- Decision Trees
- Random Forest
- K-Nearest Neighbors
- Naïve Bayes
- Content based learning approaches
- Collaborative Filtering Approaches
- Algorithms
- UBCF
- IBCF
- Overfitting Control Techniques
- Latent Factor Learning Approaches
- Top-N Recommenders
- Evaluation Metrics
- Accuracy
- Error Rate
- Rating Prediction
- RMSE
- Iterative Algorithm
- K-Means
- K-medoids
- K-Prototype
- Density based Algorithms
- DB-SCAN
- Linear PCA
- Non-linear PCA
- t-SNE
