
Learn how the and operator filters records by requiring all conditions to be true in a where clause, with practical SQL examples using age, weight, and center back players.
Use the distinct statement to find unique values in a column with select from. Practice counting players per club and per nationality by grouping and ordering results.
Master the sql replace function to substitute strings across columns like nationality, product_line, and customer_type, apply conditions with where and between dates, and alias results.
Explore the trim, ltrim, and rtrim functions in SQL to remove leading, trailing, or both spaces from strings, with practical examples and length verification.
Explore the cast and convert functions to convert values to specified data types, compare syntax and compatibility, and see MySQL examples converting char to date time and date to char.
Apply core date, day, month, and year functions in MySQL to extract day, month, year, and current date from date columns such as birth date and date sale.
Learn how subqueries, select statements embedded in a main select and enclosed in parentheses, drive queries with examples like finding max salary in France.
Explore how Python dictionaries store key-value pairs, create and access items, add and update entries with update, copy dictionaries with copy, and remove items using pop, del, or clear.
Display data frames in pandas using head and tail to view rows, inspect shape, and show all rows by using pd.set_option display.max_rows after reading a csv into a df.
Welcome to Modern Data Analyst. The role of the data analyst has evolved and now it’s not enough to know Excel to be a data analyst. In this course, we will learn how to use SQL, Python & ChatGPT for Data Analysis.
First, we'll learn SQL from scratch. SQL is a programming language that will help us work with data. We’ll use a free database for this course: MySQL. Here are some of the SQL concepts this course covers.
- Basic SQL commands and clauses (SELECT FROM, WHERE, INSERT, HAVING, UPDATE, etc)
- Aggregate functions with GROUP BY commands
- SQL Joins
- Logical operators
- Subqueries. temporary tables, rank, etc
- Projects, exercises, and more!
Then we’ll learn Python from zero. Python is used for data analysts to collect data, explore data, and make visualizations. Here's what the Python section covers.
- Python Crash Course: We'll learn all the Python core concepts such as variables, lists, dictionaries, and more.
- Python for Data Analysis: We'll learn Python libraries used for data analysis such as Pandas and Numpy. We'll use them to do data analysis tasks such as cleaning and preparing data.
- Python for Data Visualization: We'll learn how to make visualizations with Pandas.
Finally, we'll learn ChatGPT for data analysis. We’ll learn how to use ChatGPT’s code interpreter to analyze data, extract data from websites, automate Excel reports, and more.
What makes this course different from the others, and why you should enroll?
This is the most updated and complete data analysis course. 3-in-1 bundle (SQL, Python and ChatGPT)
You'll learn traditional tools as well as modern tools used in data analysis
We'll solve exercises and projects to put into practice the concepts learned
Join me now and become a data analyst.