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ZeroToMastery - Python for Business Data Analytics & Intelligence [FCO]
About
Become a top Business Data Analyst. We’ll teach you everything you need to go from a complete beginner to getting hired as an analytics professional. You’ll learn to use Python and the latest industry tools and techniques to make data-driven decisions.
Course Overview
We guarantee you this is the most up-to-date and comprehensive course on learning how to use Python and the latest industry tools and techniques for business data analysis. You'll learn analytics by using real-world data and examples, including the data used in the hit movie Moneyball, to become a top Business Data Analyst and get HIRED this year.
What You'll Learn
- The skills to become a professional Business Analyst and get hired
- Step-by-step guidance from an industry professional
- Learn to use Python for statistics, causal inference, econometrics, segmentaiton, matching, and predictive analytics
- Master the latest data and business analysis tools and techniques including Google Causal Impact, Facebook Prophet, Random Forest and much more
- Participate in challenges and exercises that solidify your knowledge for the real world
- Learn what a Business Analyst does, how they provide value, and why they're in demand
- Analyze real datasets related to Moneyball, wine quality, Wikipedia searches, employee remote work satisfaction, and more
- Learn how to make data-driven decisions
- Enhance your proficiency with Python, one of the most popular programming languages
- Use case studies to learn how analytics have changed the world and help individuals and companies succeed
Are there any prerequisites for this course?
- A computer (Windows, Mac, or Linux) with an internet connection
- Basic Python knowledge. Don't know Python? No problem, you'll get access to our Python Bootcamp here as well where we'll teach you Python from scratch
- A willingness and enthusiasm to learn and take action
Who is this course for?
- Developers that want a step-by-step guide to learn and master Business Data Analytics from scratch all the way to being able to get hired at a top company
- Students who want to go beyond all of the "beginner" Python and Data Analytics tutorials out there
- Developers that want to use their skills in a new discipline
- Programmers who want to learn one of the most in-demand skills
- Developers that want to be in the top 10% of Business Data Analysts
- Students who want to gain experience working on large, interesting datasets
- Bootcamp or online tutorial graduates that want to go beyond the basics
- Students who want to learn from an industry professional with real-world experience, not just another online instructor that teaches off of documentation
Instructor(s)
Hi, I'm Diogo Resende!
Diogo has been working for over a decade as a data scientist. He loves harnessing the power of data and analytics to understand what has happened, what will happen next, and how to use that information to your advantage.
Your instructor (Diogo) isn't just an expert with years of real-world professional experience. He has been in your shoes. He makes learning fun. He makes complex topics feel simple. He will motivate you. He will push you. And he will go above and beyond to help you succeed.
General Info:
Author(s)
: Diogo Resende
Language
: English
Updated
: 2022
Videos Duration
: 15.5 hours
Course Source
: https://zerotomastery.io/courses/learn-business-analytics/
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[FreeCoursesOnline.Me] ZeroToMastery - Python for Business Data Analytics & Intelligence
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1 Section 1 - Introduction
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Exercise_ Meet Your Classmates and Instructor.pdf (250.3 KB)
Introduction
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Introduction.mp4 (25.1 MB)
Python for Business Analytics & Intelligence
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Python for Business Analytics & Intelligence.mp4 (169.8 MB)
Setting up the Course Material
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Setting up the Course Material.mp4 (34.5 MB)
The Modern Day Business Analyst
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The Modern Day Business Analyst.mp4 (11.0 MB)
10 Section 8 - Matching
CASE STUDY - Catholic Schools & Standardized Tests (Briefing)
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CASE STUDY - Catholic Schools & Standardized Tests (Briefing).mp4 (3.5 MB)
CHALLENGE - Introduction
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CHALLENGE - Introduction.mp4 (34.8 MB)
CHALLENGE - Solutions
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CHALLENGE - Solutions.mp4 (112.2 MB)
Common Support Region
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Common Support Region.mp4 (14.2 MB)
Matching - Game Plan
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Matching - Game Plan.mp4 (5.5 MB)
Matching
My Experience with Matching
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My Experience with Matching.mp4 (5.4 MB)
Python - Chi-square Loop
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Python - Chi-square Loop.mp4 (23.2 MB)
Python - Chi-square Test
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Python - Chi-square Test.mp4 (38.8 MB)
Python - Cleaning and Preparing Dataset
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Python - Cleaning and Preparing Dataset.mp4 (28.8 MB)
Python - Common Support Region Visualization
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Python - Common Support Region Visualization.mp4 (9.1 MB)
Python - Comparing Means
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Python - Comparing Means.mp4 (20.0 MB)
Python - Directory and Libraries
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Python - Directory and Libraries.mp4 (16.7 MB)
Python - Education Variables
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Python - Education Variables.mp4 (44.2 MB)
Python - Loading Data
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Python - Loading Data.mp4 (31.3 MB)
Python - Logistic Regression and Debugging
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Python - Logistic Regression and Debugging.mp4 (92.7 MB)
Python - Matching
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Python - Matching.mp4 (43.5 MB)
Python - Other Variables
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Python - Other Variables.mp4 (23.8 MB)
Python - Outcome Visualization
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Python - Outcome Visualization.mp4 (9.1 MB)
Python - Preparing for Common Support Region
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Python - Preparing for Common Support Region.mp4 (35.0 MB)
Python - Race Variable Transformation
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Python - Race Variable Transformation.mp4 (86.1 MB)
Python - Robustness Check - Removing 1 confounder
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Python - Robustness Check - Removing 1 confounder.mp4 (29.4 MB)
Python - Robustness Check - Repeated experiments
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Python - Robustness Check - Repeated experiments.mp4 (57.4 MB)
Python - T-Test Loop
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Python - T-Test Loop.mp4 (23.8 MB)
Python - T-Test
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Python - T-Test.mp4 (26.2 MB)
Robustness Checks
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Robustness Checks.mp4 (4.6 MB)
The Curse of Dimensionality
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The Curse of Dimensionality.mp4 (5.3 MB)
Unconfoundedness
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Unconfoundedness.mp4 (5.2 MB)
11 PART C_ SEGMENTATION
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What is Segmentation and why is it important.pdf (208.5 KB)
12 Section 9 - RFM (Recency, Frequency, Monetary) Analysis
CASE STUDY - Online Shopping (Briefing)
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CASE STUDY - Online Shopping (Briefing).mp4 (1.6 MB)
CHALLENGE - Introduction
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CHALLENGE - Introduction.mp4 (10.9 MB)
CHALLENGE - Solutions
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CHALLENGE - Solutions.mp4 (38.4 MB)
Python - Applying RFM Function
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Python - Applying RFM Function.mp4 (8.6 MB)
Python - Creating Sales Variable
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Python - Creating Sales Variable.mp4 (14.3 MB)
Python - Customer Level Aggregation
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Python - Customer Level Aggregation.mp4 (21.6 MB)
Python - Date Variable
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Python - Date Variable.mp4 (11.5 MB)
Python - Directory and Libraries
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Python - Directory and Libraries.mp4 (9.7 MB)
Python - Loading Data
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Python - Loading Data.mp4 (21.2 MB)
Python - Monetary Variable
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Python - Monetary Variable.mp4 (5.2 MB)
Python - Quartiles
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Python - Quartiles.mp4 (23.0 MB)
Python - RFM Function
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Python - RFM Function.mp4 (11.4 MB)
Python - RFM Score
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Python - RFM Score.mp4 (6.6 MB)
Python - Results Summary
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Python - Results Summary.mp4 (14.9 MB)
Python - Tidying up Dataframe
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Python - Tidying up Dataframe.mp4 (12.1 MB)
RFM - Game Plan
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RFM - Game Plan.mp4 (2.3 MB)
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