Apoorva G.

Years of Experience in R Programming

7

Years of Experience in Data Analytics classes

6

Years of Experience in Data Science Classes

4

Teaching Experience in detail in Data Science Classes

The Data Science course will include the following topics Introduction to Data Science What is Data Science? The Data Science Process Importance of Data Science Data Collection and Cleaning Data Sources Data Collection Methods Data Cleaning and Preprocessing Exploratory Data Analysis (EDA) Descriptive Statistics Data Visualization Outlier Detection Data Preprocessing Handling Missing Data Feature Engineering Data Transformation Machine Learning Basics Introduction to Machine Learning Supervised vs. Unsupervised Learning Model Training and Evaluation Supervised Learning Algorithms Linear Regression Logistic Regression Decision Trees and Random Forests Support Vector Machines Naive Bayes Unsupervised Learning Algorithms Model Evaluation and Hyperparameter Tuning Model Metrics (Accuracy, F1 Score, etc.) Jupyter Notebooks (Python) / Studio (R) Real-world Projects and Case Studies Applying Data Science to Real Problems Data Science Career Paths Online Courses and Books Data Science Communities and Forums Conclusion and Next Steps