IBM Data Analyst Complete Course | Data Analyst Tutorial For Beginners,

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Build job-ready skills by learning from the best. This IBM Data Analyst Complete Course provides a structured learning path covering the modern data ecosystem, the role of data analysts, data repositories, data gathering, wrangling, analysis, and communication. It includes Excel basics for data analysis, data visualization and dashboards using Excel and Cognos, Python fundamentals for data science, projects, SQL for data science, data analysis with Python, data visualization with Python, and a capstone project. Key timestamps: 0:00:00 Modern Data Ecosystem and the Role of data analytics; 0:21:48 The Data Analyst Role; 0:39:39 The Data Ecosystem and Language for Data Professionals; 1:08:41 Understanding Data Repositories and Big Data platforms; 1:47:03 Gathering Data; 2:03:47 Wrangling Data; 2:26:55 Analyzing and Mining Data; 2:46:33 Communicating Data Analysis Findings; 3:11:19 Opportunities and Learning Paths; 3:40:06 Introduction to Spreadsheets for Data Analysis; 4:06:37 Getting Started Using Spreadsheets; 4:42:03 Basics of Data Quality and Privacy; 5:01:55 Cleaning Data; 5:30:02 Data Analysis Basics Filtering and Sorting Data; 6:05:57 Using Pivot Tables; 6:26:48 Creating Charts; 6:50:32 Creating Advanced Charts; 7:04:27 Creating Dashboards Using Spreadsheets; 7:21:39 Creating Dashboards using IBM Cognos Analytics; 7:35:08 Types; 7:38:11 Expressions and Variables; 7:42:06 String Operations; 7:46:04 Lists and Tuples; 7:54:56 Dictionaries; 7:57:21 Sets; 8:02:39 Conditions and Branching; 8:12:56 Loops; 8:19:42 Functions; 8:33:14 Exception Handling; 8:37:03 Objects and Classes; 8:47:56 Reading Writing files with open; 8:54:34 Pandas; 8:59:43 Numpy in Python; 9:18:21 Simple APIs; 9:28:41 REST APIs Webscraping and Working with Files; 9:51:59 Optional Intro to Webscraping; 10:01:58 Basic SQL; 10:20:58 Introduction to Relational Databases and tables; 10:43:05 Refining your Results; 10:53:59 Functions Multiple Tables and Sub Queries; 11:14:43 Accessing Databases Using Python; 11:41:55 Assignment Preparing working with real world data sets and build in SQL; 11:54:53 View Stored Procedures and Transactions; 12:05:41 Join Statements; 12:18:16 Import Datasets; 12:38:02 Data Wrangling; 12:57:26 Exploratory Data Analysis; 13:17:06 Model Development; 13:44:31 Model Evaluation and Refinement; 14:05:42 Welcome; 14:10:13 Introduction to Data Visualization; 14:32:21 Basic Visualization tools; 14:45:36 Specialized Visualization tools; 14:58:24 Advanced Visualization tools; 15:03:48 Visualization Geospatial Data; 15:13:06 Creating dashboards with plotly and dash; 15:30:37 Welcome to the Course; 15:33:49 How to Present your Findings.