DATA SCIENCE WITH PYTHON

COURSE DESCRIPTION

This bootcamp covers the essentials of Data Science, from basic Python programming to advanced machine learning techniques. Participants will learn through practical exercises and end with a capstone project.

LEARNING OBJECTIVES

Gain proficiency in Python and its key libraries for Data Science. Understand and apply statistical methods to real-world data.

Develop and evaluate predictive models using machine learning. Complete a data science project from start to finish.

INTENDED AUDIENCE

Aspiring data scientists, analysts, or anyone interested in entering the field of data science. Professionals looking to integrate data science into their current roles.

PREREQUISITES

Basic understanding of programming concepts. Familiarity with fundamental statistics is helpful but not required.

COVERED TOPICS

Python Programming, Data Manipulation and Visualization, Statistical Analysis- Basic and Advanced Machine Learning.

COURSE OUTLINE

DAY 1: Introduction to Data Science and Python Basics
Session 1: Introduction to Data Science
• Overview of Data Science: Definitions, significance, and real-world applications.
• Key components of Data Science: Data exploration, data cleaning, model building, and deployment.
• Tools and Software Introduction: Python, Jupyter Notebooks, Colab.
Session 2: Setting Up the Data Science Environment
• Installation of Python and essential libraries (NumPy, Pandas, Matplotlib, Scikit-learn).
• Introduction to Jupyter Notebook: Features, advantages, and creating your first notebook.
Session 3: Python for Data Science
• Python syntax and basic constructs: Variables, data types, functions, and conditional statements.
• Introduction to NumPy: Array operations, indexing, and broadcasting

DAY 2: Data Manipulation and Visualization
Session 1: Data Manipulation with Pandas
• Introduction to Pandas: DataFrames, Series.
• Dataimporting/exporting, cleaning, and transformation techniques.
• Advanced Pandas operations: Merging, joining, and concatenating.
Session 2: Data Visualization Techniques
• Introduction to Matplotlib: Plot types, customization options.
• Introduction to Seaborn: Statistical data visualization, heatmaps, and pair plots.

DAY 3: Statistical Analysis and Machine Learning Basics
Session 1: Statistics for Data Science
• Descriptive statistics: Mean, median, mode, variance.
• Probability distributions and hypothesis testing.
• Correlation vs. causation: Understanding the difference and importance.
Session 2: Introduction to Machine Learning
• Supervised learning: Regression and classification tasks.
• Unsupervised learning: Clustering and dimensionality reduction.
• Hands-on: Building a linear regression model using Scikit-learn.

DAY 4: Advanced Machine Learning
Session 1: Advanced ML Techniques
• Decision Trees and Random Forests: Theory and practice.
• Support Vector Machines: Concept and applications.
• Overfitting and underfitting: Techniques to manage model performance.
Session 2: Model Evaluation and Ensemble Methods
• Cross-validation, ROC curves, and area under the curve (AUC).
• Ensemble methods: Bagging, boosting, and stacking.
• Practical exercises: Implementing ensemble techniques on a dataset.

DAY 5: Machine Learning Project and Career Advancement
Session 1: Capstone Project Work
• Application of full data science pipeline: From data cleaning to model deployment.
• Group projects: Participants will be divided into small groups to tackle a Real-world problem using data science.
Session 2: Project Presentations and Discussion
• Groups present their findings and models.
• Feedback session: Review and critique of projects to foster improvement and learning.
• Discussion on next steps in Data Science, continuing education, and career opportunities
• Each day includes practical exercises and interactive discussions to ensure a comprehensive learning experience.

This detailed breakdown helps participants prepare for what to expect each day and allows them to track their progress throughout the bootcamp

For FULL COURSE OUTLINE, please contact us. Please contact us for the schedules and for booking a private class.

Inquire Now