Please register using below form or this link: https://form.jotform.com/240716625877062
Please register using below form or this link: https://form.jotform.com/240716625877062
June 10th to July 9th.
Note: No Sessions on July 4th and 5th due to Forth of July Holiday.
Day 1-2: Introduction to Python for Data Science
Basics of Python programming.
Introduction to Jupyter Notebooks.
Day 3-4: Data Manipulation with Pandas
Reading and writing data with Pandas.
Basic data manipulation techniques.
Day 5: Data Analysis and Visualization Basics
Introduction to data analysis concepts.
Basic plots with Matplotlib and Seaborn.
Assignment 1: Complete a set of exercises on Python basics, Pandas data manipulation, and create a basic data visualization.
Day 6-7: Advanced Data Analysis
Advanced Pandas techniques.
More complex data visualizations.
Day 8-9: NumPy for Numerical Data
Deep dive into NumPy for array and matrix operations.
Day 10: Introduction to Machine Learning
Overview of machine learning, supervised vs. unsupervised learning.
Assignment 2: Perform advanced data analysis and visualization on a given dataset, summarizing insights.
Day 11-13: Supervised Learning Algorithms and scikit-learn
Linear Regression, Logistic Regression, and Decision Trees.
Building models with scikit-learn.
Day 14-15: Unsupervised Learning Algorithms and scikit-learn
K-Means Clustering, Hierarchical Clustering, and PCA.
Introduction to model evaluation techniques.
Assignment 3: Build and evaluate a supervised model and an unsupervised model using scikit-learn on provided datasets.
Day 16-17: Natural Language Processing with NLTK
Basics of NLP.
Text preprocessing and basic tasks with NLTK.
Day 18-20: BootCamp Final Project
Application of learned concepts to a real-world dataset.
Data preprocessing, exploratory data analysis, and model building.
Final Project: Complete a comprehensive project that involves data cleaning, exploratory analysis, and building a predictive machine learning model.