Data Analysis Bootcamp™ 21 Real World Case Studies
- 4.4
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Brief Introduction
Gain Business Intelligence Skills using Statistics, Data Wrangling, Data Science, Visualizations & Google Data StudioDescription
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:
The Importance of Data Analytics
Python Crash Course
Data Manipulations and Wrangling with Pandas
Probability and Statistics
Hypothesis Testing
Data Visualization
Geospatial Data Visualization
Story Telling with Data
Google Data Studio Dashboard Design - Complete Course
Machine Learning - Supervised Learning
Machine Learning - Unsupervised Learning (Clustering)
Practical Analytical Case Studies
Google Data Studio Dashboard & Visualization Project:
Executive Sales Dashboard (Google Data Studio)
Python, Pandas & Data Analytics and Data Science Case Studies:
Health Care Analytics & Diabetes Prediction
Africa Economic, Banking & Systematic Crisis Data
Election Poll Analytics
Indian Election 2009 vs 2014
Supply-Chain for Shipping Data Analytics
Brent Oil Prices Analytics
Olympics Analysis - The Greatest Olympians
Home Advantage Analysis in Basketball and Soccer
IPL Cricket Data Analytics
Predicting the Soccer World Cup
Pizza Resturant Analytics
Bar and Pub Analytics
Retail Product Sales Analytics
Customer Clustering
Marketing Analytics - What Drives Ad Performance
Text Analytics - Airline Tweets (Word Clusters)
Customer Lifetime Values
Time Series Forecasting - Demand/Sales Forecast
Airbnb Sydney Exploratory Data Analysis
A/B Testing
Requirements
- Requirements
- Familiar with basic programming concepts
- Highschool level math knowledge
- Broadband Internet connection
Knowledge
- 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
Rajeev D. Ratan
4.4 Raiting
Data Analysis Bootcamp™ 21 Real World Case Studies
- 4.4
-
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