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Get started in the sought-after field of data analysis with a Professional Certificate from IBM. Learn the core principles of data analysis and gain experience in manipulating data with Python and Excel, applying analytical techniques and working with a variety of data sources.

Course material: https://mega.nz/file/HBYViQRb#P7X4-tPnJjhDu5gEtEO5VIV8PrrO-sEy-yT26mEHvUg

An alternative link to access the file: https://drive.google.com/file/d/1rjbNTknDaOpOcfd6Yn36IXMQoyrgu3Qm/view?uspsharing

Database technology from Meta: https://youtu.be/iwRneX7GIGI
Applied Data Science from IBM: https://youtu.be/AMtFSAt0tZ0
Applied Data Science with R from IBM: https://youtu.be/5phPXk1ypZE

TIME STAMP

INTRODUCTION TO DATA ANALYSIS
0:00:00 Modern data ecosystem and the role of data analytics
0:21:48 The role of the data analyst
0:39:39 The data ecosystem and the language for data professionals
1:08:41 Understanding data storage and big data platforms
1:47:03 Collecting data
2:03:47 Organize data
2:26:55 Analyze and evaluate data
2:46:33 Communication of the results of the data analysis
3:11:19 Opportunities and learning paths

EXCEL BASICS FOR DATA ANALYSIS
3:40:06 Introduction to spreadsheets for data analysis
4:06:37 Getting started with spreadsheets
4:42:03 Basics of data quality and data protection
5:01:55 Clean up data
5:30:02 Basics of data analysis Filtering and sorting data
6:05:57 Using pivot tables

DATA VISUALIZATION AND DASHBOARDS EXCEL AND COGNOS
6:26:48 Creating diagrams
6:50:32 Creating advanced charts
7:04:27 Creating dashboards using spreadsheets
7:21:39 Creating dashboards with IBM Cognos Analytics

PYTHON FOR DATA SCIENCE, AI & DEVELOPMENT
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 sentences
8:02:39 Conditions and branches
8:12:56 Grinding
8:19:42 Features
8:33:14 Exception handling
8:37:03 Objects and classes
8:47:56 Reading Writing files with open
8:54:34 Panda
8:59:43 Numpy in Python
9:18:21 Simple APIs
9:28:41 REST APIs, web scraping and working with files

PYTHON PROJECT FOR DATA SCIENCE
9:51:59 Optional introduction to web scraping

DATABASES AND SQL FOR DATA SCIENCE WITH PYTHON
10:01:58 Basic SQL
10:20:58 Introduction to relational databases and tables
10:43:05 Refine your results
10:53:59 Functions Multiple tables and subqueries
11:14:43 Accessing databases with Python
11:41:55 Task preparation: Working with real data sets and integrating them into SQL
11:54:53 View stored procedures and transactions
12:05:41 Join statements

DATA ANALYSIS WITH PYTHON
12:18:16 Import records
12:38:02 Data preparation
12:57:26 Exploratory data analysis
13:17:06 Model development
13:44:31 Model evaluation and refinement

DATA VISUALIZATION WITH PYTHON
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 of geodata
15:13:06 Creating dashboards with Plotly and Dash

IBM DATA ANALYST CAPSTONE PROJECT
15:30:37 Welcome to the course
15:33:49 How to present your results

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