With so much to learn and so many advancements to follow in the field of data science, there are a core set of foundational concepts that remain essential. Twenty of these ideas are highlighted here that are key to review when preparing for a job interview or just to refresh your appreciation of the basics.With so much to learn and so many advancements to follow in the field of data science, there are a core set of foundational concepts that remain essential. Twenty of these ideas are highlighted here that are key to review when preparing for a job interview or just to refresh your appreciation of the basics.
- Dataset
- Data Wrangling
- Data Visualization
- Outliers
- Data Imputation
- DataScaling
- Principal Component Analysis (PCA)
- Linear Discriminant Analysis (LDA)
- Data Partitioning
- Supervised Learning
- Unsupervised Learning
- Reinforcement Learning
- Model Parameters and Hyperparameters
- Cross-validation
- Bias-variance Tradeoff
- Evaluation Metrics
- Uncertainty Quantification
- Math Concepts
- Statistics and Probability Concepts
- Productivity Tools