📊 Data Analytics Bootcamp Portfolio

Welcome to my collection of projects and assignments from the Data Analytics Bootcamp.

---

Labs&Projects

📁 1: Prework for the Ironhack Data Analytics Bootcamp

• Prework

📁 2: First Project

• Text RPG Game-Python

📁 3: List comprehensions

• Lab | List Comprehensions

📁 4: Dicts, Sets and Tuples

• Lab | Dicts, Sets, and Tuples

📁 5: String Operations

• Lab | String Operations and Bag of Words

📁 6: Numpy

• Lab | Numpy Deep Dive

📁 7: Intro to Pandas

• Lab | Introduction to Pandas

📁 8: My First Queries

• Lab | My first queries

📁 9: MySQL Select

• Lab | MySQL Select

📁 10: MySQL Advanced

• Lab | Advanced MySQL

📁 11: Dataframe Calculations

• Lab | Dataframe Calculation and Transformation

📁 12: Advanced Pandas

• Lab | Advanced Topics with Pandas

📁 13: Importing and Exporting Data

• Lab | Importing and Exporting Files

📁 14: Data Cleaning

• Lab | Data Cleaning

📁 15: Lambda Functions

• Lab | Lambda Functions

📁 16: Map, Reduce, Filter (Optional)

• Lab | Map, Reduce, Filter

📁 17: SQL Project

• Project Bootcamps

📁 18: API Scavanger Game

• Lab | API Scavenger Game

📁 19: Mini-project - Part 1 (Optional)

• Mini-Project | Module 2 Cumulative Lab 1

📁 20: Web Scraping

• Lab | Web Scraping

📁 21: Pandas Deep Dive

• Lab | Pandas Deep Dive

📁 22: Advanced Regex

• Lab | Advanced Regular Expressions

📁 23: Matplotlib and Seaborn

• Lab | Matplotlib and Seaborn Deep Dive

📁 24: Code Simplicity and Efficiency (Optional)

• Lab | Code Simplicity and Efficiency

📁 25: Project WebScrapping

• Project Data Thieves

📁 26: Introduction to BI and Tableau

• Lab | Introduction to BI and Tableau

📁 27: BI Analysis with Tableau

• Lab | BI Analysis with Tableau

📁 28: Tableau Advanced Charts (Optional)

• Lab | Tableau advanced charts

📁 29: Tableau Dashboard Mini Project

• Lab | Tableau Dashboard Mini Project- London Crime

📁 30: Pivot Tables

• Lab | Pivot Table and Correlations

📁 31: Descriptive Statistics

• Lab | Understanding descriptive stats

📁 32: Subsetting and Descriptive Statistics

• Lab | Subsetting and Descriptive Stats

📁 33: Linear Regression

• Lab | Regression Analysis

📁 34: Mini-project - Part 2 EDA (Optional (Continuation of the point 19) )

• Mini-Project | Module 2 Cumulative Lab 1

📁 35: Introduction to Probability

• Lab | Probability Introduction

📁 36: Probability Distributions

• Lab | Discrete and Continuous Probability Distributions

📁 37: Hypothesis Testing Mini-Project

• Lab | Inferential Statistics Review

📁 38: Confidence Intervals

• Lab | Confidence Intervals

📁 39: Hypothesis Testing

• Lab 1 | Hypothesis Testing
• Lab 2 | Hypothesis Testing

📁 40: Intro to Scipy

• Lab | Introduction to SciPy

📁 41: Two Sample Hypothesis Tests

• Lab | Two Sample Hypothesis Testing

📁 42: Goodness of Fit

• Lab | Goodness of Fit and Independence Tests

📁 43: Project . Hypothesis Testing

• Melbourne-RealEstate

📁 44: Parallelization (Optional)

• Lab | Parallelization

📁 45: Bayesian Statistics (Optional)

• Lab | Intro to Bayesian Statistics

📁 46: Project Data collection and analysis

• Project Guidelines
• My Project- Lisbon-Parking

📁 47: Intro to Machine Learning

• Lab | Introduction to Machine Learning and ML Workflow

📁 48: Supervised Learning

• Lab | Supervised Learning

📁 49: Supervised Learning with Scikit-learn

• Lab | Supervised Learning with Scikit-Learn

📁 50: Imbalance

• Lab | Imbalance between classes

📁 51: Problems in Machine Learning

• Lab | Problems with Machine Learning

📁 52: Project - Hackaton

• Shop Revenue Prediction Task

📁 53: Unsupervised Learning

• Lab | Unsupervised Learning

📁 54: Unsupervised Learning with Sckit-Learn

• Lab | Unsupervised Learning with Scikit-Learn

📁 55: Deep Learning

• Lab | Neural Networks

📁 56: Natural Language Processing

• Lab | Natural Language Processing

---

Final Project 🎓

• Water potability prediciton App