The Data Analyst Course: Complete Data Analyst Bootcamp 2023

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Akhil Vydyula

16:43:45

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1. Introduction to Data Analytics

1.1 Course Content - Became a Data Analyst.pdf

1. Course Content - Became a Data Analyst.mp4

04:24

2.1 Common Mistakes in Data Analytics.html

2. How not to Learn Data Analytics Tools.mp4

05:54

2. Structured Query Language (SQL)

1. Introduction to SQL - SQL Syntax and Download MySQL.mp4

08:17

2. RDBMS - Data Integrity, Database Normalization.mp4

22:15

3. Data Definition Language (DDL).mp4

22:15

4. Data Manipulation language (DML).mp4

19:32

5. Data Control Languages (DCL) and Domain Constraints.mp4

23:10

6. Filtering Data and SET Operators in SQL.mp4

21:31

7. Conditional Expressions in SQL.mp4

23:45

8. Grouping Data.mp4

29:21

9. Joining Multiple Tables (JOINS).mp4

16:43

10. SQL RANK Functions.mp4

18:47

11. SQL Triggers and Stored Procedures.mp4

31:16

12. Data Analytics on Movie Reviews in SQL.mp4

38:27

3. Statistical Analysis

1.1 Business Statistics.pptx

1. Introduction to statistics and Measures of central tendencies.mp4

15:41

2.1 tutorial_stats_pel.zip

2. Central Limit Theorem.mp4

30:18

3. Distributions and Correlations.mp4

51:02

4.1 data_cleaning_insights.zip

4.2 data.csv

4. PDF & CDF and Hypothesis Testing.mp4

40:34

5.1 basics_of_time_series_forecasting.zip

5.2 Time_Series_AirPassengers.csv

5. Time Series Forecasting.mp4

52:43

6. Probability Theory and Statistical Analysis.mp4

01:09:37

7.1 uk_road_accident_analytics.zip

7. Capstone Project - UK Road Accident Analysis (Part - 1).mp4

32:20

8.1 uk_road_accident_timeseries_forecasting.zip

8. Capstone Project - UK Road Accident (Part -2).mp4

28:54

4. Microsoft Excel

1. Introduction to Excel Workbook.mp4

50:38

2. Hands on Excel Cells and Ranges.mp4

19:43

3. Basic Formulae - Logical Operators.mp4

17:01

4. Excel - Lookup and Reference Formulae.mp4

23:29

5. Excel - Logical Formulae.mp4

11:33

6. Text and Statistical Formulae.mp4

26:40

7. Excel - Date & Time Formulae.mp4

15:34

8. Excel - Sorting & Filtering.mp4

16:52

9. Dynamic Charts With Examples.mp4

11:54

10. Derive Insights with Pivot Tables.mp4

11:20

5. Microsoft Power BI (Business Intelligence Tool)

1. Installation Power BI Desktop and Applications of Power BI.mp4

26:27

2. Understand the Concepts of Maps using Power BI.mp4

14:11

3. Power BI - Tables and Matrix.mp4

27:31

4. Different Types of Power BI Slicers.mp4

22:26

5. Introduction to Power Query.mp4

21:49

6. Hands on with Power Query Operations.mp4

19:05

7. Manipulations with Power Query Operations.mp4

14:52

8. Build a Sales Dashboard.mp4

24:17

9. Capstone Project - Sales and Production Analysis.mp4

21:37

Description

Data Science involves: Statistics, Excel, Linear Algebra, Power BI, Machine Learning, SQL

What You'll Learn?

Learn how to create pie, bar, line, area, histogram, scatter, regression, and combo charts
Learn how to obtain interesting, real-time information from Excel,Power BI,SQL.
Understand different data types and their memory usage
Expand your knowledge of NumPy – statistics and preprocessing
Solve a final capstone project

Who is this for?

You should take this course if you want to become a Data Analyst and Data Scientist

This course is for you if you want a great career

The course is also ideal for beginners, as it starts from the fundamentals and gradually builds up your skills

More details

Description
In business, being able to understand, harness, and use data is no longer a skill reserved for a handful of well-paid analysts. It's becoming an essential part of many roles.
If that sounds daunting, don't worry. There is a growing set of tools designed to make data analysis accessible to everyone, in this huge-value, four-course Data Analysts Toolbox bundle we look in detail at three of those tools: Excel, Python, and Power BI.
In isolation Excel, Python, and Power BI are useful and powerful. Learn all three and you are well on your way to gaining a much deeper understanding of how to perform complex data analysis.
This Data Analysts Toolbox bundle is aimed at intermediate Excel users who are new to Python and Power BI. All courses include practice exercises so you can put into practice exactly what you learn.

Power Pivot, Power Query and DAX
How to get started with Power Query
How to connect Excel to multiple workbooks
How to get data from the web and other sources
How to merge and append queries using Power Query
How the Power Pivot window works
How to set up and manage relationships in a data model
How to create a PivotTable to display your data from the Power Pivot data model
How to add calculated columns using DAX
How to use functions such as CALCULATE, DIVIDE, DATESYTD in DAX
All about creating Pivot Charts and PivotTables and using your data model
How to use slicers to adjust the data you display

Power BI
What is Power BI and why you should be using it.
To import CSV and Excel files into Power BI Desktop.
How to use Merge Queries to fetch data from other queries.
How to create relationships between the different tables of the data model.
All about DAX including using the COUTROWS, CALCULATE, and SAMEPERIODLASTYEAR functions.
All about using the card visual to create summary information.
How to use other visuals such as clustered column charts, maps, and trend graphs.
How to use Slicers to filter your reports.
How to use themes to format your reports quickly and consistently.
How to edit the interactions between your visualizations and filter at visualization, page, and report level.
Who this course is for:
You should take this course if you want to become a Data Analyst and Data Scientist
This course is for you if you want a great career
The course is also ideal for beginners, as it starts from the fundamentals and gradually builds up your skills

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Hi There!My Name is Akhil Vydyula, I am a Data Scientist I was previously worked on BFSI data analysis and modelling skills to oversee the full-life cycle of development and execution. He possess strong.ability to data wrangling, feature engineering, algorithm development, model training and implementation.SKILLS AND COMPETENCIESExpert knowledge and experience with C/C++/python Programming and SQL.Should be able to learn and Implement new technologies quickly and effectively.Excellent Mathematical Skills, Problem Solving & Logical Skills.Actively Participating in hackathons in various platforms and writing blogs in medium.TECHNICAL SKILLSMachine Learning, Natural Language Processing(NLP),Computer Vision,Regression, Multi LabelClassification.Transfer Learning, Transformers, Ensembles, Stacking Classifiers.AutoML, SQL, Python, Keras, Pandas, NumPy, Seaborn,Matplotlib,Clustering,Recommendation Systems,Time Series Analysis.

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