Business Analyst Bootcamp: Excel, Stats, SQL, Tableau
Business Analyst Bootcamp: Excel, Stats, SQL, Tableau, available at $64.99, has an average rating of 4.53, with 95 lectures, 4 quizzes, based on 465 reviews, and has 1901 subscribers.
You will learn about Excel: Mine data and generate actionable insights with Pivot Tables, Lookup Functions, Index/Match, and Graphs Excel: Create machine learning model and make predictions with Analysis Toolpak SQL: Understanding the data life cycle and how data moves from a pipeline into a data warehouse/lake SQL: Query, clean, and prepare data for analysis and real-time reporting Tableau: Create visualizations and dashboards to communicate data insights Tableau: Storytelling technical information to executives and business stakeholders This course is ideal for individuals who are University/College students who want to enter the workforce as a business analyst or prepare for a course or Experienced professionals who want to improve data literacy, implement agile practices, or do a career pivot or Small business owners who want to implement data-drive decision making in their operations or Businesses looking to enrol new business analysts in a data training bootcamp It is particularly useful for University/College students who want to enter the workforce as a business analyst or prepare for a course or Experienced professionals who want to improve data literacy, implement agile practices, or do a career pivot or Small business owners who want to implement data-drive decision making in their operations or Businesses looking to enrol new business analysts in a data training bootcamp.
Enroll now: Business Analyst Bootcamp: Excel, Stats, SQL, Tableau
Summary
Title: Business Analyst Bootcamp: Excel, Stats, SQL, Tableau
Price: $64.99
Average Rating: 4.53
Number of Lectures: 95
Number of Quizzes: 4
Number of Published Lectures: 95
Number of Published Quizzes: 4
Number of Curriculum Items: 126
Number of Published Curriculum Objects: 126
Original Price: $39.99
Quality Status: approved
Status: Live
What You Will Learn
- Excel: Mine data and generate actionable insights with Pivot Tables, Lookup Functions, Index/Match, and Graphs
- Excel: Create machine learning model and make predictions with Analysis Toolpak
- SQL: Understanding the data life cycle and how data moves from a pipeline into a data warehouse/lake
- SQL: Query, clean, and prepare data for analysis and real-time reporting
- Tableau: Create visualizations and dashboards to communicate data insights
- Tableau: Storytelling technical information to executives and business stakeholders
Who Should Attend
- University/College students who want to enter the workforce as a business analyst or prepare for a course
- Experienced professionals who want to improve data literacy, implement agile practices, or do a career pivot
- Small business owners who want to implement data-drive decision making in their operations
- Businesses looking to enrol new business analysts in a data training bootcamp
Target Audiences
- University/College students who want to enter the workforce as a business analyst or prepare for a course
- Experienced professionals who want to improve data literacy, implement agile practices, or do a career pivot
- Small business owners who want to implement data-drive decision making in their operations
- Businesses looking to enrol new business analysts in a data training bootcamp
Welcome to my Business Analytics/Intelligence course with over 30+ practical examples!
With the meteoric rise of AI-based technologies, the world of work is changing once again to demand data-driven decisions as industries scramble to become agile and augment with new technology. In this course, I will teach you ALL of the necessary skills using free tools such as Google Sheets (Excel, Analysis ToolPak), MySQL, and Tableau (trial)!
This is an introductory self-paced course with an MBA-level curriculum tailored to suit students from all backgrounds! Whether you’re currently a student preparing for the job market, a seasoned professional looking to up-skill / pivot, or a business owner looking to accelerate your growth, you will finish this course with a fundamentally different understanding of how the world operates today.
Our course will consist of theoretical videos, hands-on tutorials where we work through short assignments together, and mock cases to dive into a wide range of topics, including data pipelines, intro/advanced spreadsheets functions + tools, descriptive/inferential statistics, machine learning, time series, SQL, visualization, and nontechnical skills.
I will be constantly updating this course with industry breakthroughs regularly, and adjusting materials based on student feedback to provide an optimized learning experience.
By the end of this course, you’ll have a comprehensive understanding of Business Analytics and how to use various tools and techniques to analyze data and make informed business decisions.
So, what exactly will you be learning? Here’s a brief breakdown of the course units:
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Introduction:Welcome to the course where you’ll learn about how agile and AI-powered workflows enable the modern agile business analyst.
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Data Pipeline:You’ll learn about big data and how data is collected, stored, and organized.
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Spreadsheets & Descriptive Statistics: You’ll explore spreadsheets and descriptive statistics, understanding normal distributions and relationships between data points.
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Probability:You’ll study random variables and probability distributions, calculating statistics and making decisions.
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Inferential Statistics:You’ll dive into inferential statistics, learning about hypothesis testing and decision making based on expected value.
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Machine Learning 1: You’ll be introduced to machine learning and artificial intelligence, including linear and non-linear regressions.
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Time Series:You’ll forecast with time series and predict future events.
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Machine Learning 2: You’ll learn about classification, clustering, and reinforcement learning.
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SQL:You’ll understand databases, reading, changing and working with multiple tables.
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Visualization & Presentation:You’ll study business intelligence, creating visualizations (Tableau) and presenting data effectively.
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Non-Technical Skills: You’ll evaluate businesses and work within teams, prioritizing projects and understanding KPIs.
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Conclusion:Quick wrap up of everything that you have learned
Are you ready to dive into the world of Business Analytics? Let’s get started!
Shoutout to Mike Yang for dev reviews
Course Curriculum
Chapter 1: Introduction
Lecture 1: What will we learn?
Lecture 2: What do BAs do?
Lecture 3: What is agile software development?
Lecture 4: What are the different types of analytics?
Lecture 5: What is the role of AI in modern workflows?
Lecture 6: Why do we use living documents and mobile apps?
Lecture 7: What are no-code/low-code softwares?
Chapter 2: Data Pipeline
Lecture 1: What is big data?
Lecture 2: What are data pipelines?
Lecture 3: How is data collected?
Lecture 4: What kinds of data are there?
Lecture 5: How is data stored?
Chapter 3: Spreadsheets & Descriptive Statistics
Lecture 1: What are spreadsheets?
Lecture 2: What are spreadsheet functions?
Lecture 3: What are descriptive statiistics?
Lecture 4: What is a normal distribution?
Lecture 5: How do we filter and organize information?
Lecture 6: How do we characterize data point relationships?
Lecture 7: Exotic Excursions Solution
Lecture 8: Global Travellers Solution
Lecture 9: Histogram Solution
Lecture 10: Stationary Sales Solution
Lecture 11: Company Roles Solution
Lecture 12: Tutoring Company Solution
Lecture 13: Customer Orders Solution
Chapter 4: Probability
Lecture 1: What are random variables and probability distributions?
Lecture 2: How are statistics calculated for random variables?
Lecture 3: What are probability distributions?
Lecture 4: How do we make decisions based on expected value?
Lecture 5: Bachelor Degrees Solution
Lecture 6: Shop Visitors Solution
Lecture 7: Grocery Defects Solution
Lecture 8: Car Dealership Solution
Lecture 9: Grade Calculator Solution
Chapter 5: Inferential Statistics
Lecture 1: What are inferential statistics?
Lecture 2: What are hypotheses?
Lecture 3: What are error types?
Lecture 4: How do we know if our hypothesis is true (pt 1)?
Lecture 5: How do we know if our hypothesis is true (pt 2)?
Lecture 6: What types of hypothesis tests exist?
Lecture 7: What is A/B testing?
Lecture 8: Coffee Store Solution
Lecture 9: Travel Consultant Solution
Lecture 10: Marketing Page Solution
Lecture 11: Golf Manufacturer Solution
Chapter 6: Machine Learning 1
Lecture 1: What is machine learning and artificial intelligence?
Lecture 2: Why do we need to clean our data?
Lecture 3: What is linear regression?
Lecture 4: What are multiple linear regressions?
Lecture 5: How do we compare models?
Lecture 6: What are non-linear regressions?
Lecture 7: Linear Regression Solution
Lecture 8: Outlier Removal Solution
Lecture 9: Baby Height Solution
Lecture 10: Multiple Regression Solution
Lecture 11: Admission Rates Solution
Chapter 7: Machine Learning 2
Lecture 1: What is classification?
Lecture 2: What is clustering?
Lecture 3: How do we make clusters?
Lecture 4: How do we optimize clusteriing?
Lecture 5: What is reinforcement learning?
Lecture 6: What is model fit?
Chapter 8: Time Series
Lecture 1: What is forecasting with time series?
Lecture 2: How do we predict with time series?
Lecture 3: Weekly Grades Solution
Lecture 4: Quarterly Sales Solution
Lecture 5: 5 Year Plan Solution
Instructors
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Leo Zhu
Product Manager & Instructor
Rating Distribution
- 1 stars: 3 votes
- 2 stars: 6 votes
- 3 stars: 27 votes
- 4 stars: 122 votes
- 5 stars: 307 votes
Frequently Asked Questions
How long do I have access to the course materials?
You can view and review the lecture materials indefinitely, like an on-demand channel.
Can I take my courses with me wherever I go?
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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