Udemy – Complete Data Analyst Bootcamp From Basics To Advanced

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Description

Are you ready to embark on a rewarding career as a Data Analyst? Whether you’re a beginner or an experienced professional looking to enhance your skills, this Complete Data Analyst Bootcamp is your one-stop solution. This course is meticulously designed to equip you with all the essential tools and techniques needed to excel in the field of data analysis.

What You Will Learn:

  1. Python Programming for Data Analysis
    Dive into Python, the most popular programming language in data science. You’ll learn the basics, including data types, control structures, and how to manipulate data with powerful libraries like Pandas and NumPy. By the end of this module, you’ll be able to perform complex data manipulations and basic analyses with ease.

  2. Statistics for Data Science
    Understanding the language of data requires a solid foundation in statistics. This course will take you through the key concepts such as descriptive statistics, probability, hypothesis testing, and inferential statistics. You’ll gain the confidence to make data-driven decisions and interpret statistical results accurately.

  3. Feature Engineering and Data Preprocessing
    Data preparation is critical for successful analysis. This module covers all aspects of feature engineering, from handling missing data and encoding categorical variables to feature scaling and selection. Learn how to transform raw data into meaningful features that improve model performance and analysis outcomes.

  4. Exploratory Data Analysis (EDA)
    Before diving into data modeling, it’s crucial to understand your data. EDA is the process of analyzing data sets to summarize their main characteristics, often with visual methods. You’ll learn how to identify trends, patterns, and outliers using visualization tools like Matplotlib and Seaborn. This step is essential for uncovering insights and ensuring data quality.

  5. SQL for Data Analysts
    SQL (Structured Query Language) is the backbone of database management and a must-have skill for any data analyst. This course will guide you from the basics of SQL to advanced querying techniques. You’ll learn how to retrieve, manipulate, and aggregate data efficiently using SQL Server, enabling you to work with large datasets and perform sophisticated data analysis.

  6. Power BI for Data Visualization and Reporting
    Data visualization is key to communicating your findings effectively. In this module, you’ll master Power BI, a leading business intelligence tool. You’ll learn how to create compelling dashboards, perform data transformations, and use DAX (Data Analysis Expressions) for complex calculations. The course also includes real-world reporting projects, allowing you to apply your skills and create professional-grade reports.

  7. Real-World Capstone Projects
    Put your knowledge to the test with hands-on capstone projects. You’ll work on real-world datasets to perform end-to-end data analysis, from data cleaning and EDA to creating insightful visualizations and reports in Power BI. These projects are designed to simulate actual industry challenges, giving you practical experience that you can showcase in your portfolio.

Who Should Enroll:

  • Aspiring data analysts looking to build a comprehensive skill set from scratch.

  • Professionals seeking to switch careers into data analysis.

  • Data enthusiasts who want to gain hands-on experience with Python, SQL, and Power BI.

  • Students and recent graduates aiming to enhance their job prospects in the data science industry.

Why This Course?

  • Comprehensive Curriculum: Covers everything from Python programming and statistics to SQL and Power BI, making you job-ready.

  • Hands-On Learning: Work on real-world projects that mirror the challenges you’ll face in the industry.

  • Industry-Relevant Tools: Learn the most in-demand tools and technologies, including Python, SQL Server, and Power BI.

  • Career Support: Gain access to valuable resources and guidance to help you kickstart or advance your career as a data analyst.

Conclusion:

By the end of this course, you’ll have a strong foundation in data analysis and the confidence to tackle real-world data problems. You’ll be ready to step into a data analyst role with a robust portfolio of projects to showcase your skills.

Enroll now and start your journey to becoming a proficient Data Analyst!

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What Will You Learn?

  • Python နဲ့အတူ Pandas, NumPy, Matplotlib, Seaborn လို အာနိသင်ပြည့်မီတဲ့ libraries တွေကို အသုံးချပြီး Data တွေကို ထိရောက်စွာ ပြောင်းလဲခြင်း၊ ခွဲခြမ်းစိတ်ဖြာခြင်းနဲ့ မြင်သာအောင်ဖော်ပြခြင်းတို့ကို ထိထိရောက်ရောက်လုပ်နိုင်ဖို့ လေ့လာသင်ယူရပါမယ်။
  • SQL ကို အသုံးပြုပြီး Data ကို ရယူခြင်း၊ ပြောင်းလဲခြင်း၊ စုစည်းခြင်း စွမ်းရည်တွေကို အဆင့်မြင့်တိုးတက်အောင် သင်ယူရမယ်။ Database တွေကို စီမံခန့်ခွဲရာမှာ SQL Server ကို အသုံးပြုပြီး အဆင့်မြင့် query တွေ လည်း run တတ်အောင် သင်ယူရပါမယ်။
  • Exploratory Data Analysis (EDA) ကို လေ့လာပြီး Data ထဲက အမြင်အသစ်တွေရှာဖွေခြင်း၊ Pattern တွေသိရှိခြင်းနဲ့ နောက်ထပ် ခွဲခြမ်းစိတ်ဖြာမှုအတွက် Data တွေကို ပြင်ဆင်ခြင်း လုပ်ဆောင်ပုံများကို သင်ယူရမယ်။ Visualization နည်းလမ်းတွေနဲ့ ထိရောက်အောင်ဖော်ပြခြင်းများကို လုပ်ဆောင်ရပါမယ်။
  • Power BI ကို အသုံးချပြီး interactive dashboards တွေတည်ဆောက်နိုင်သည့်အပြင် DAX ကို အသုံးပြုပြီး အဆင့်မြင့်တွက်ချက်မှုများ လည်း လုပ်ဆောင်နိုင်မယ်။ နောက်ထပ် အမှန်တကယ်အကျိုးရှိတဲ့ Data တွေနဲ့ ချိတ်ဆက်ပြီး အကျိုးပြုစာရင်းများ ထုတ်ပေးနိုင်မယ့် နည်းလမ်းများကိုလည်း သင်ယူရပါမယ်။

Course Content

Udemy – Complete Data Analyst Bootcamp From Basics To Advanced

  • 18:20
  • 18:40
  • 03. Complete Python With Important Libraries
    07:02:03
  • 04. Data Analysis With Python
    02:26:33
  • 05. Getting Started With Statistics
    01:32:55
  • 06. Descriptive Statistics
    02:38:46
  • 07. Probability Distribution Function And Types OF Distribution
    03:00:33
  • 08. Inferential Stats And Hypothesis Testing
    02:31:13
  • 09. Feature Engineering With Python
    01:23:47
  • 10. Exploratory Data Analysis
    01:38:43
  • 24:46
  • 12. Microsoft SQL Server basics
    09:03:12
  • 13. SQL Basics Questions
    01:26:35
  • 14. SQL Assignments
  • 15. SQL Functions
    01:26:06
  • 16. Advanced SQL
    01:39:04
  • 17. SQL Important Interview Questions
    57:32
  • 10:59
  • 16:06
  • 20. Data Visualization
    02:22:22
  • 21. Power Query Editor
    02:12:16
  • 22. DAX
    02:09:45
  • 23. Power BI Project 1, Sales Data Analysis
    03:39:30
  • 24. Power BI Project 2, Insurance Data Analysis
    02:22:22
  • 25. Power BI Project 3, UPI Transactions Data Analysis
    01:30:21
  • 22:36
  • 27. Getting Started with Microsoft Excel
    02:42:17
  • 28. Excel Dashboard 1
    01:24:51
  • 29. Excel Dashboard 2
    01:21:55
  • 30. Power Query Editor (MS Excel)
    02:04:57
  • 34:48
  • 32. Tableau
    02:40:18
  • 35:59
  • 34. Tableau Dashboard 2
    35:29
  • 35. Tableau Prep Builder
    01:26:49
  • 36. SQL + Tableau Project (Student Depression Data Analysis)
    01:27:19
  • 37. Snowflake
    01:09:36
  • 08:47
  • 39. AWS + Snowflake + Power BI Project
    01:10:17
  • 40. AWS + Snowflake + Tableau Project
    01:06:11
  • 41. New End to End Power BI Project 1 (Data Source Dataflow)
    04:33:51
  • 42. New End to End Power BI Project 2 (Datasource MYSQL Database & SQL Server)
    02:12:07
  • 43. New End to End Power BI Project 3 (Datasource Google Big Query)
    02:46:51
  • 44. New End to End Power BI Project 4 (Data Source Azure SQL Database)
    01:57:49
  • 45. –PROJECTS USING AI TOOLS–
  • 46. New Power BI Project Using AI Tools
    01:47:28
  • 14:13

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