Data Analysis Bootcamp™ 21 Real World Case Studies
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
Description
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
Who this course is for:
- Begineers to Data Anaysis
- Business Analysts who wish to do more with their data
- College graduates who lack real worlde experience
- Business oriented persons (Management or MBAs) who'd like to use data to enhance their skills
- Software Developers or Engineers who'd like to move into a Data Analyst Career
- Anyone looking to understand Data and uncover insights
- Those looking for a good foundation before starting a Data Science Masters/Bootcamp
Course content
- Preview07:22
- Preview09:53
- Preview06:37
- 07:27Making Sense of Buzz Words, Data Science, Big Data, Machine & Deep Learning
- 04:50The Roles in the Data World - Analyst, Engineer, Scientist, Statistician, DevOps
Instructors
![Rajeev D. Ratan](data:image/svg+xml,%3Csvg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 64 64"%3E%3C/svg%3E){kind=avatar}
- 4.4 Instructor Rating
- 7,242 Reviews
- 46,972 Students
- 7 Courses
Hi I'm Rajeev, a Data Scientist, and Computer Vision Engineer.
I have a BSc in Computer & Electrical Engineering and an MSc in Artificial Intelligence from the University of Edinburgh where I gained extensive knowledge of machine learning, computer vision, and intelligent robotics.
I have published research on using data-driven methods for Probabilistic Stochastic Modeling for Public Transport and even was part of a group that won a robotics competition at the University of Edinburgh.
I launched my own computer vision startup that was based on using deep learning in education since then I've been contributing to 2 more startups in computer vision domains and one multinational company in Data Science.
Previously, I worked for 8 years at two of the Caribbean’s largest telecommunication operators where he gained experience in managing technical staff and deploying complex telecommunications projects.
- 4.4 Instructor Rating
- 2,240 Reviews
- 38,586 Students
- 6 Courses
Nidia has a diverse background as her undergraduate studies include Computer Science at The University of Derby, England and Civil & Environmental Engineering at The University of the West Indies. Her current research involves using NLP to analyse open-source data and opinion mining solutions within the Social Sciences. She is currently enrolled to continue her postgraduate studies at Kings College London in 2021.