This online Data Analyst course is designed to transform you into a skilled analytics professional. You’ll master the latest tools and techniques, work with SQL, R, and Python, create impactful data visualizations, and apply statistics and predictive analytics to solve real-world business challenges.
Earn a prestigious Data Analyst Master’s certificate
Participate in live sessions conducted by experienced faculty
Gain insights directly from IBM industry experts
Earn additional IBM credentials for select courses
Interact with IBM leadership through exclusive AMA events
Work on 20+ projects and capstone assignments across 3 domains
Participate in IBM-led hackathons to showcase your skills
Enjoy unlimited access to self-paced course materials
Master SQL from basic queries to advanced concepts
Get certified in Data Analysis with industry-recognized program. Gain expert insights through masterclasses and AMAs, earn dual certifications, complete real-world capstone projects, and fast-track your career growth!
This Data Analyst course is ideal for anyone interested in building a career in data analytics. It is well-suited for:
No prior experience in data analysis is required. However, having the following will be an advantage:
0.01 Introduction
1.01 Introduction to Business Analytics
1.02 Data Analyst
1.03 Knowledge Check
2.01 Data Cleaning and Preparation
2.02 Knowledge Check
3.01 Conditional Formatting and Important Functions
3.02 Knowledge Check
4.01 Analyzing Data with Pivot Tables
4.02 Knowledge Check
5.01 Dashboarding
5.02 Knowledge Check
6.01 Analytics with Excel
6.02 Knowledge Check
7.01 Data Analysis using Statistics
7.02 Knowledge Check
8.01 Macros for Analytics
8.02 Knowledge Check
1.01 Course Introduction
2.01 Introduction
2.02 Introduction to Databases
2.03 Introduction to Database Management System
2.04 DBMS vs. RDBMS
2.05 Introduction to MySQL
2.06 Tables in MySQL
2.07 Relationships in MySQL
2.08 Views in MySQL
2.09 Table vs. Views
2.10 Quick Recap
3.01 Introduction
3.02 Entity Relationship Model
3.03 Attributes
3.04 Relationship Set and Degree
3.05 Types of Relationship
3.06 Mapping Cardinalities
3.07 Database Normalization
3.08 Types of Anomalies
3.09 Types of Normalization
3.10 Types of Normalization: One NF, Two NF, and Three NF
3.11 Types of Normalization: BCNF, Four NF, and Five NF
3.12 Recap
4.01 Introduction
4.02 Downloading MySQL Community Setup
4.03 Installing MySQL Community
4.04 Configuring MySQL Community and Workbench
4.05 Connecting to MySQL Server
4.06 Downloading Sample MySQL Database in MySQL Workbench
4.07 Recap
5.01 Introduction
5.02 Database Manipulation in MySQL
5.03 Transactions and ACID Properties in MySQL
5.04 MySQL Storage Engines
5.05 Creating and Managing Tables in MySQL
5.06 Creating and Managing Tables: CREATE, DESCRIBE, and SHOW Table
5.07 Creating and Managing Tables: ALTER, TRUNCATE, and DROP Tables
5.08 Inserting and Querying Data in Tables
5.09 Filtering Data from Tables in MySQL
5.10 Filtering Data: WHERE and DISTINCT Clauses
5.11 Filtering Data: AND and OR Operators
5.12 Filtering Data: IN and NOT IN Operators
5.13 Filtering Data: BETWEEN and LIKE Operators
5.14 Filtering Data: LIMIT, IS NULL, and IS NOT NULL Operators
5.15 Sorting Table Data
5.16 Grouping Table Data and Roll Up in MySQL
5.17 Comments in MySQL
5.18 Recap
5.19 Spotlight
6.01 Introduction
6.02 Operators in MySQL
6.03 Indexing in MySQL
6.04 Order of Execution in MySQL
6.05 Assisted Practice Constraint
6.06 Data Types in MySQL
6.07 Recap
7.01 Introduction
7.02 Understanding SQL Functions
7.03 Aggregate Functions
7.04 Scalar Functions
7.05 String Functions
7.06 Numeric Functions
7.07 Date and Time Functions
7.08 Handling Duplicate Records
7.09 Miscellaneous Functions
7.10 General Functions
7.11 Recap
7.12 Spotlight
8.01 Introduction
8.02 Introduction to Alias
8.03 Introduction to JOINS
8.04 Right, Cross, and Self Join
8.05 Operators in MySQL
8.06 Intersect and Emulation
8.07 Minus and Emulation
8.08 Subquery in SQL
8.09 Subqueries with Statements and Operators
8.10 Subqueries with Commands
8.11 Derived Tables in SQL
8.12 EXISTS Operator
8.13 NOT EXISTS Operator
8.14 EXISTS vs. IN Operators
8.15 Recap
9.01 Introduction
9.02 Introduction to Window Function
9.03 Window Function Syntax
9.04 Aggregate Window Functions
9.05 Ranking Window Functions
9.06 Miscellaneous Window Functions
9.07 Miscellaneous Window Functions: FIRST VALUE, NTH VALUE, and NTILE
9.08 Miscellaneous Window Functions: CUME DIST, LEAD, LAG, and LAST VALUE
9.09 Recap
9.10 Spotlight
10.01 Introduction
10.02 SQL Views and Manipulation Methods
10.03 Altering and Renaming Views
10.04 View Processing Algorithms
10.05 Updatable Views
10.06 Creating Views Using With Check Option Local
10.07 Creating Views Using With Cascaded Check Option
10.08 Creating Views Using With Local Check Option
10.09 Recap
11.01 Introduction
11.02 Introduction to Stored Procedures
11.03 Advantages of Stored Procedures
11.04 Working With Stored Procedures
11.05 Compound Statements
11.06 Conditional Statements
11.07 IF Statement
11.08 IF-THEN Statement
11.09 IF-THEN-ELSE Statement
11.10 IF-THEN-ELSE-IF ELSE Statement
11.11 Case Statement
11.12 Simple Case Statement
11.13 Searched Case Statement
11.14 Loops in Stored Procedures
11.15 Loop Statement
11.16 While Loop
11.17 Repeat Loop
11.18 Leave Statement
11.19 Using Leave with Stored Procedures
11.20 Using Leave with Loop Statement
11.21 Using Leave with While Loop
11.22 Using Leave with Repeat Loop
11.23 Error Handling in Stored Procedures
11.24 Raising Errors in Error Handling
11.25 Cursors in Stored Procedures
11.26 Steps to Use Cursors
11.27 Stored Functions in Stored Procedures
11.28 Stored Program Security
11.29 SQL Trigger
11.30 Recap
11.31 Spotlight
12.01 Introduction
12.02 Execution Plan in SQL
12.03 Differences Between CHAR, VARCHAR, and NVARCHAR
12.04 Index Guidelines and Clustered Indexes in MySQL
12.05 Common Table Expression
12.06 MySQL Best Practices
12.07 Recap