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Data Analysis Bootcamp™ 21 Real World Case Studies

Gain Business Intelligence Skills using Statistics, Data Wrangling, Data Science, Visualizations & Google Data Studio
Instructor:
Rajeev D. Ratan
4,348 students enrolled
English [Auto]
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 Data Studio 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/B Testing

Course Introduction & the Importance of Data Analysts

1
Course Introduction
2
The Importance of Data Analyst
3
Why Data is the new Oil
4
Making Sense of Buzz Words, Data Science, Big Data, Machine & Deep Learning
5
The Roles in the Data World - Analyst, Engineer, Scientist, Statistician, DevOps

Download Code and Slides and Setup Google Colab

1
Download Code and Slides
2
Download Course Code, Slides and Setup Google Colab for your iPython Notebooks

You can find all the course Code in the Resources section of this chapter.



Python Crash Course

1
Why use Python for Data Anakytics and Data Science?
2
Python - Basic Variables
3
Python - Array/Lists and Dictionaries
4
Python - Conditional Statements
5
Python - Loops
6
Python - Functions
7
Python - Classes

Pandas - Data Series and Manipulation

1
Introduction to Pandas
2
Pandas 1 - Data Series
3
Pandas 2A - DataFrames - Index, Slice, Stats, Finding Empty cells, Filtering
4
Pandas 2B - DataFrames - Index, Slice, Stats, Finding Empty cells & Filtering

Pandas - Data Cleaning & Aggregration

1
Pandas 3B - Data Cleaning - Alter Colomns/Rows, Missing Data & String Operations
2
Pandas 3A - Data Cleaning - Alter Colomns/Rows, Missing Data & String Operations
3
Pandas 4 - Data Aggregation - GroupBy, Map, Pivot, Aggreate Functions

Pandas - Feature Engineering & Joins/Merge/Concatenating

1
Pandas 5 - Feature Engineer, Lambda and Apply
2
Pandas 6 - Concatenating, Merging and Joinining

Pandas - Time Series Data

1
Pandas 7 - Time Series Data

Advanced Pandas

1
Pandas 7 - ADVANCED Operations - Iterows, Vectorization and Numpy
2
Pandas 8 - ADVANCED Operations - More Map, Zip and Apply
3
Pandas 9 - Advanced Operations - Parallel Processing

Map Visualizations

1
Map Visualizations with Plotly - Cloropeths from Scratch - USA and World
2
Map Visualizations with Plotly - Heatmaps, Scatter Plots and Lines

Statistics for Data Analysts & Visualizations

1
Introduction to Statistics
2
Descriptive Statistics - Why Statistical Knowledge is so Important
3
Descriptive Statistics 1 - Exploratory Data Analysis (EDA) & Visualizations
4
Descriptive Statistics 2 - Exploratory Data Analysis (EDA) & Visualizations
5
Sampling, Averages & Variance And How to lie and Mislead with Statistics
6
Variance, Standard Deviation and Bessel’s Correction
7
Types of Variables - Quantitive and Qualitative
8
Frequency Distributions
9
Frequency Distributions Shapes
10
Analyzing Frequency Distributions - What is the Best Type of Wine? Red or White?
11
Covariance & Correlation - Do Amazon & Google know you better than anyone else?
12
Sampling - Sample Sizes & Confidence Intervals - What Can You Trust?
13
Mean, Mode and Median - Not as Simple As You'd Think
14
The Normal Distribution & the Central Limit Theorem
15
Lying with Correlations – Divorce Rates in Maine caused by Margarine Consumption
16
Z-Scores

Probability Theory

1
Probability - An Introduction
2
Estimating Probability
3
Addition Rule
4
Permutations & Combinations
5
Bayes Theorem

Hypothesis Testing

1
Hypothesis Testing Introduction
2
Statistical Significance
3
Hypothesis Testing – P Value
4
Hypothesis Testing – Pearson Correlation

Google Data Studio - Introduction & Setup

1
All about Google Data Studio
2
Opening Google Data Studio and Uploading Data

Google Data Studio - Your First Dashboard

1
Your First Dashboard Part 1
2
Your First Dashboard Part 2
3
Creating New Fields

Google Data Studio - Pivot & Dynamic Tables (with Filters)

1
Pivot Tables
2
Dynamic Filtered Tables

Google Data Studio - Scorecards and Time Comparison

1
Scorecards
2
Scorecards with Time Comparison

Google Data Studio - Bar Charts, Line Charts and Time Series Plots

1
Bar Charts
2
Line Charts
3
Time Series and Comparitive Time Series Plots

Google Data Studio - Pie charts, Donut Charts, Treemaps & Scatter Plots

1
Pie Charts, Donut Charts and Tree Maps
2
Scatter Plots

Google Data Studio - Geographic & Map Plots

1
Google Data Studio - Geographic & Map Plots

Google Data Studio - Bullet and Line Area Plots

1
Google Data Studio - Scatter Plots

Google Data Studio - Sharing your Interactive Dashboards

1
Google Data Studio - Sharing your Interactive Dashboards

Retail Sales Dashboard for Executives

1
Homework Project - Create Executive Sales Dashboard

Introduction to Machine Learning

1
How Machine Learning enables Computers to Learn
2
What is a Machine Learning Model?
3
Types of Machine Learning

Linear Regressions

1
Linear Regression – Introduction to Cost Functions and Gradient Descent
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Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don't have an internet connection, some instructors also let their students download course lectures. That's up to the instructor though, so make sure you get on their good side!
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15 hours on-demand video
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Full lifetime access
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Certificate of Completion
Data Analysis Bootcamp™ 21 Real World Case Studies
Category:
Business
Teacher
Daniel W
Price:
$218.98 $149
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