The Complete Data Analyst Course: From Zero to Data Hero! (Master the Fundamentals of Data Analysis)

Are you ready to start your journey as a data analyst? This course, "The Complete Data Analyst Course: From Zero to Data Hero," is designed to take you from a complete beginner to an expert, even if you have no experience in data analysis or coding. With the growing demand for data analysts and high-paying job opportunities, this course provides a comprehensive learning experience that covers everything from the basics to advanced techniques. You'll gain essential skills in data analysis, Excel, Python, and SQL, and you'll even be introduced to machine learning.

Throughout "The Complete Data Analyst Course: From Zero to Data Hero," you'll engage with over 80 high-quality video lectures, hands-on projects, and practical exercises that mimic real-world scenarios. You'll master Excel for data manipulation and visualization, learn Python programming and data handling with Pandas, and create stunning visualizations with Matplotlib and Seaborn. Additionally, you'll dive into SQL to manage and analyze databases and connect Python to SQL for complex data queries.

This course has resources to support your learning, including comprehensive code notebooks, downloadable slides, theory notes, and coding challenges to test your knowledge. Whether you're a beginner or looking to enhance your skills, this course will help you build a strong foundation and become a confident, skilled data analyst. Get ready to transform your career and start making data-driven decisions like a pro!

The Complete Data Analyst Course: From Zero to Data Hero Table of Contents:

1. The Complete Data Analyst Course: From Zero to Data Hero! - 05:04
2. Read Before Starting - 00:23
3. Introduction to Data Analysis - 09:16
4. Types of Data & The Data Analysis Stages - 10:11
5. Quiz: Categorising Data / Types of Data (6 questions)
6. Data Analyst vs. Data Scientist & Career Path - 05:59
7. Introduction to Excel - 06:25
8. Excel Basics - 09:26
9. Basic Formulas and Functions - 16:00
10. Importing Data - 05:40
11. Sorting Data - 06:10
12. Filtering Data - 05:23
13. What-if Analysis (Goal Seek + Scenario Manager) - 07:00
14. Conditional Formatting - 05:09
15. Additional Excel Tools - 12:29
16. Data Analysis Addon Pack - 08:46
17. Ultimate LOOKUP Tutorial (VLOOKUP, HLOOKUP, XLOOKUP) - 09:35
18. Conditional Functions (IF, IFERROR, Nested Functions and More!) - 08:48
19. Text-based Functions Part 1 (LEFT, MID, RIGHT) - 07:22
20. Text-based Functions Part 2 (TRIM, CONCAT, LEN) - 05:30
21. Date-time Functions - 05:52
22. Mathematical Functions Part 1 (COUNTIF, SUMIF, COUNTA) - 06:26
23. Mathematical Functions Part 2 (SEQUENCE, LARGE/SMALL, RANK and More!) - 06:38
24. The Importance of Data Visualisation & Creating our First Chart - 16:05
25. Chart Formatting + Chart Elements - 09:48
26. Additional / Advanced Chart Types - 08:11
27. Introduction to PivotTable - 10:56
28. PivotTable Formatting - 09:56
29. PivotCharts - 09:55
30. Cleaning Data with Microsoft Excel - 29:09
31. Data Analysis / EDA with Microsoft Excel - 30:39
32. Python / Anaconda Installation - 06:51
33. Anaconda & Jupyter Notebook Overview - 07:42
34. Data Types, Variables and Printing - 18:48
35. Data Structures and Operators - 18:40
36. If / Else-if / Else Statements, Loops and Functions - 20:08
37. Lambda Expressions, Map/Filter/Reduce and Modules - 13:48
38. Python Practice Activities - 03:10
39. Python Practice Activities Solutions - 19:08
40. Introduction to NumPy - 02:26
41. NumPy Arrays (ndarrays) - 22:40
42. Indexing and Slicing - 12:37
43. Universal Functions and Other Array Manipulations - 04:42
44. NumPy Practice Activities Overview - 01:32
45. NumPy Practice Activities Solutions - 13:25
46. Introduction to Pandas - 02:13
47. Data Structures - Series - 12:08
48. Data Structures - DataFrames (Part 1) - 14:20
49. Data Structures - DataFrames (Part 2) - 08:16
50. Grouping and Sorting Data - 09:41
51. Missing Data - 06:40
52. Combining Datasets - 13:16
53. Dataset Operations - 09:49
54. Pandas Practice Activities Overview - 02:02
55. Pandas Practice Activities Solutions - 15:14
56. Introduction to Matplotlib - 02:30
57. Matplotlib Fundamentals - 08:22
58. Exploring Different Plot Types - 16:55
59. Plot Customisation and Styling - 10:18
60. Figures and Subplots - 16:22
61. Matplotlib Practice Activities Overview - 03:10
62. Matplotlib Practice Activities Solutions - 12:04
63. Introduction to Seaborn - 02:31
64. Seaborn Fundamentals - 16:43
65. Categorical Plots - 10:55
66. Matrix Plots - 16:18
67. Grid Plots - 09:43
68. Styling and Colour - 06:10
69. Seaborn Practice Activities Overview - 03:22
70. Seaborn Practice Activities Solutions - 07:25
71. Project Introduction and Loading our Data - 07:55
72. Cleaning our Data with Python - 19:57
73. Exploratory Data Analysis with Python (Part 1) - 10:43
74. Exploratory Data Analysis with Python (Part 2) - 13:07
75. Python Portfolio Project Overview - 03:55
76. Python Portfolio Project Solutions - 28:19
77. Introduction to Machine Learning - 09:46
78. Preparing our Data - 17:09
79. Creating our Machine Learning Model (Logistic Regression) - 12:18
80. Introduction to Databases and SQL - 07:59
81. Installing SQL Server + Importing our Data - 11:48
82. Querying Data with SQL: FROM, SELECT and WHERE - 15:02
83. Effective SQL: Joins, Grouping, and Aggregate Functions - 23:19
84. Exporting Data from SQL - 09:02
85. Congratulations & Next Steps - 05:39
86. Accessing & Downloading your Certificate - 00:03

Who is this course for?

1. Perfect for beginners with no prior experience who want to start a career in data analysis.
2. It is ideal for professionals in other fields looking to switch to a data analysis role.
3. Excellent for students or recent graduates in any field who want to learn valuable data analysis skills.
4. Great for anyone interested in collecting, analyzing, and visualizing data to uncover insights.

Click on the links below to Download The Complete Data Analyst Course: From Zero to Data Hero!