Class Central is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Udemy

Data Analysis Bootcamp™ 21 Real World Case Studies

via Udemy

Overview

Gain Business Intelligence Skills using Statistics, Data Wrangling, Data Science, Visualizations & Google Data Studio

What you'll learn:
  • Understand the value of data for businesses
  • The importance of Data Analytics
  • The role of a Data Analyst
  • Learn to use Python, Pandas, Matplotlib & Seaborn, Scikit-learn
  • Learn Visualization Tools such as Matplotlib, Seaborn, Plotly and Mapbox
  • Hypothesis Testing and A/B Testing - Understand t-tests and p values
  • Unsupervised Machine Learning with K-Means Clustering
  • Machine Learning from Linear Regressions (polynomial & multivariate), K-NNs, Logistic Regressions, SVMs, Decision Trees & Random Forests
  • Advanced Pandas techniques from Vectorizing to Parallel Processsng
  • Statistical Theory, Probability Theory, Distributions, Exploratory Data Analysis
  • Ananlytic Case Studies involving Retail, Health, Elections, Sports, Resturants, Airbnb, Uber and more!
  • Full Tutorial on Google Data Studio for Dashboard Creation

Data Analysts aim to discover how data can be used to answer questions and solve problems through the use of technology. Many believe this will be the job of the future and be the single most important skill a job application can have in 2020.

In the last two decades, the pervasiveness of the internet and interconnected devices has exponentially increased the data we produce. The amount of data available to us is Overwhelming and Unprecedented. Obtaining, transforming and gaining valuable insights from this data is fast becoming the most valuable and in-demand skill in the 21st century.

In this course, you'll learn how to use Data, Analytics, Statistics, Probability, and basic Data Science to give an edge in your career and everyday life. Being able to see through the noise within data, and explain it to others will make you invaluable in any career.

We will examine over 2 dozen real-world data sets and show how to obtain meaningful insights. We will take you on one of the most up-to-date and comprehensive learning paths using modern-day tools like Python, Google Colab and Google Data Studio.

You'll learn how to create awesome Dashboards, tell stories with Data and Visualizations, make Predictions, Analyze experiments and more!

Our learning path to becoming a fully-fledged Data Analyst includes:

  1. The Importance of Data Analytics

  2. Python Crash Course

  3. Data Manipulations and Wrangling with Pandas

  4. Probability and Statistics

  5. Hypothesis Testing

  6. Data Visualization

  7. Geospatial Data Visualization

  8. Story Telling with Data

  9. Google DataStudio Dashboard Design - Complete Course

  10. Machine Learning - Supervised Learning

  11. Machine Learning - Unsupervised Learning (Clustering)

  12. Practical Analytical Case Studies

Google Data Studio Dashboard &Visualization Project:

  1. Executive Sales Dashboard (Google Data Studio)

Python, Pandas &Data Analytics and Data Science Case Studies:

  1. Health Care Analytics & Diabetes Prediction

  2. Africa Economic, Banking & Systematic Crisis Data

  3. Election Poll Analytics

  4. Indian Election 2009 vs 2014

  5. Supply-Chain for Shipping Data Analytics

  6. Brent Oil Prices Analytics

  7. Olympics Analysis - The Greatest Olympians

  8. Home Advantage Analysis in Basketball and Soccer

  9. IPL Cricket Data Analytics

  10. Predicting the Soccer World Cup

  11. Pizza Resturant Analytics

  12. Bar and Pub Analytics

  13. Retail Product Sales Analytics

  14. Customer Clustering

  15. Marketing Analytics - What Drives Ad Performance

  16. Text Analytics - Airline Tweets (Word Clusters)

  17. Customer Lifetime Values

  18. Time Series Forecasting - Demand/Sales Forecast

  19. Airbnb Sydney Exploratory Data Analysis

  20. A/BTesting




Syllabus

  • Course Introduction & the Importance of Data Analysts
  • Download Code and Slides and Setup Google Colab
  • Python Crash Course
  • Pandas - Data Series and Manipulation
  • Pandas - Data Cleaning & Aggregration
  • Pandas - Feature Engineering & Joins/Merge/Concatenating
  • Pandas - Time Series Data
  • Advanced Pandas
  • Map Visualizations
  • Statistics for Data Analysts & Visualizations
  • Probability Theory
  • Hypothesis Testing
  • Google Data Studio - Introduction & Setup
  • Google Data Studio - Your First Dashboard
  • Google Data Studio - Pivot & Dynamic Tables (with Filters)
  • Google Data Studio - Scorecards and Time Comparison
  • Google Data Studio - Bar Charts, Line Charts and Time Series Plots
  • Google Data Studio - Pie charts, Donut Charts, Treemaps & Scatter Plots
  • Google Data Studio - Geographic & Map Plots
  • Google Data Studio - Bullet and Line Area Plots
  • Google Data Studio - Sharing your Interactive Dashboards
  • Retail Sales Dashboard for Executives
  • Introduction to Machine Learning
  • Linear Regressions
  • Classification - Logistic Regression, SVM, Decision Trees, Random Forets & KNN
  • Assessing Model Performance
  • Neural Networks Overview
  • Unsupervised Learning
  • Dimensionality Reduction
  • Case Study 1 - Airbnb Sydney Exploratory Data Analysis
  • Case Study 2 - Retail Product Sales Analytics
  • Case Study 3 - Marketing Analytics - What Drives Ad Performance
  • Case Study 4 - Customer Clustering for Travel Agency Customers
  • Case Study 5 - Text Analytics - Airline Tweets (Word Clusters)
  • Case Study 6 - Customer Lifetime Value (CLV)
  • Case Study 7 - Health Care Analytics - Predict Diabetes
  • Case Study 8 - Africa Economic, Banking & Systematic Crisis Data
  • Case Study 9 - 2016 US President Election Analysis
  • Case Study 10 - Election Results Analysis - Indian Election 2009 vs 2014
  • Case Study 11 - Supply-Chain for Shipping Data Analytics
  • Case Study 12 - Sports Analytics - Olypmics Analysis - The Greatest Olympians
  • Case Study 13 - Home Advantage Analysis in Basketball and Soccer
  • Case Study 14 - IPL Cricket Data Analytics
  • Case Study 15 - Predicting the World Cup Winner (Soccer/Football)
  • Case Study 16 - Pizza Resturants Analysis
  • Case Study 17 - Brewery and Pub Analysis
  • Case Study 18 - EDA and Forecasting Brent Oil Prices
  • Case Study 19 - Time Series Forecasting for Sales
  • Case Study 20 - Predicting Insurance Premiums
  • Case Study 21 – A/B Testing

Taught by

Rajeev D. Ratan and Lonely Pineapple AI Studios | Nidia Sukhu | Automation Engineer/LLM Specialist

Reviews

4.6 rating at Udemy based on 1242 ratings

Start your review of Data Analysis Bootcamp™ 21 Real World Case Studies

Never Stop Learning.

Get personalized course recommendations, track subjects and courses with reminders, and more.

Someone learning on their laptop while sitting on the floor.