English | MP4 | AVC 1920×1080 | AAC 44KHz 2ch | 541 Lessons (88h 44m) | 48.94 GB
Master Data Analysis: Python, Stats, Gen AI, EDA, AWS, SQL ,Excel, Power BI, Tableau,ETL,Snowflake & Feature Engineering
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:
- 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. - 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. - 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. - 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. - 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. - 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. - 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!
Who this course is for:
- Individuals looking to start a career in data analysis and gain a comprehensive skill set from the ground up.
- Professionals from other fields who want to transition into data analysis and need a structured, all-inclusive learning path.
- Those pursuing degrees in fields like computer science, statistics, business, or related areas who want to enhance their job prospects with practical, industry-relevant skills.
- Anyone with an interest in data, who wants to learn how to analyze, visualize, and make data-driven decisions, whether for professional development or personal projects.
- Individuals already in the data industry or related fields who wish to sharpen their skills, learn new tools like Python, SQL, and Power BI, and take on more advanced data analysis tasks.
Table of Contents
Introduction To The Course
1 What Does A Data Analyst Do and Its Roadmap
Getting Started With Python
2 Getting Started With Google Colab
3 Installation Of Anaconda And Visual Studio Code
Complete Python With Important Libraries
4 Getting Started With VS Code With Environments
5 Python Basics-Syntax And Semantics
6 Variables In Python
7 Basic Data Types In Python
8 Operators In Python
9 Conditional Statements(if,elif,else)
10 Loops In Python
11 List And List Comprehrension In Python
12 Tuples In Python
13 Sets In Python
14 Dictionaries In Python
15 REal World Usecases Of List
16 Getting Started With Functions
17 More Coding Examples With Functions
18 Lambda functions
19 Map functions In Python
20 Filter Function In Python
21 Import Modules And Packages In Python
22 Standard Library Overview
23 File Operation In Python
24 Working With File Paths
25 Exception Handling With Try Except else finally blocks
Data Analysis With Python
26 Numpy In Python
27 Pandas-DataFrame And Series
28 Data Manipulation With Pandas And Numpy
29 Reading Data From Various Data Source Using Pandas
30 Data Visulaization With Matplotlib
31 Data Visualization With Seaborn
Getting Started With Statistics
32 Introduction To Statistics
33 Types Of Statistics
34 Population And Sample Data
35 Types Of Sampling Techniques
36 Types Of Data
37 Scales Of Measurement Of Data
Descriptive Statistics
38 Measure Of Central Tendency(Mean,Median And Mode)
39 Measures Of Dispersion(Range,Variance,Standard Deviation)
40 Why Sample Variance is divided by n-1
41 Random Variables
42 Percentiles And Quartiles
43 Number Summary
44 Histogram And Skewness
45 Covariance And Correlation
Probability Distribution Function And Types OF Distribution
46 Pdf, PMF, CDF
47 Types OF Probability Distribution
48 Bernoulli Distribution
49 Binomial Distribution
50 Poisson Distribution
51 Normal or Gaussian Distribution
52 Standard Normal Distribution
53 Uniform Distribution
54 Log Normal Distribution
55 Power Law Distribution
56 Pareto Distribution
57 Central Limit Theorem
58 Estimates
Inferential Stats And Hypothesis Testing
59 Hypothesis Testing And Mechanism
60 P value And Hypothesis Testing
61 Z test Hypothesis Testing
62 Student t Distribution
63 T stats With T Test and Hypothesis Testing
64 Z test vs T test
65 Type1 And Type 2 Error
66 Baye’s Theorem
67 Confidence Interval And Margin Of Error
68 What is Chi Square Test
69 Chi Square Goodness Of Fitness
70 What is Anova
71 Assumptions Of Anova
72 Types Of Annova
73 Partioning OF Annova
Feature Engineering With Python
74 Feature Engineering-Handling Missing Data
75 Feature Engineering-Handling Imbalanced Dataset
76 Feature Engineering-SMOTE
77 Handling Outliers With Python
78 Data Encoding-Nominal – One Hot Encoding
79 Label And Ordinal Encoding
80 Target Guided Ordinal Encoding
Exploratory Data Analysis
81 Red Wine Dataset EDA
82 EDA Flight Price Dataset
83 Part 1-Data Cleaning Google Playstore Dataset
84 Part 2-EDA Google Play Store Dataset
SQL – Course Introduction & Overview
85 SQL Course Introduction
86 SQL Overview
87 SQL Server Download & Install
Microsoft SQL Server basics
88 SQL Select Statement
89 SQL Select Distinct
90 SQL Temporary Tables
91 SQL Where Clause
92 SQL Order By Clause
93 SQL AND & OR Operator
94 SQL NOT, BETWEEN & IN Operators
95 SQL Insert Into
96 SQL Null Operator
97 SQL Update Statement
98 Delete, Drop & Truncate
99 SQL Comments & TOP N
100 SQL MAX & Group BY
101 SQL MIN Function & Group BY
102 SUM, AVG, COUNT & Group BY
103 Group BY Concept
104 Group BY Example SQL Server
105 SQL Having Clause
106 SQL Where & Having Clause Difference
107 Inner Join Concept
108 Inner Join Example
109 Left Join Concept
110 Left Join Example
111 Right Join Concept
112 Right Join Example
113 Left & Right Anti Join
114 Left & Right Anti Join Example
115 Full Outer Join
116 Self Join
117 Union & Union All
118 SQL Like Operator
119 SQL Case in Select statement & Order BY Clause
120 Nested CASE statement
121 SQL Data Types
122 SQL Create Table
123 Inserting Records into All Columns of the Table
124 Inserting Records into Certain Columns in a Table
125 Copying Data From One Table to Another
126 Sub Queries
127 Not Null Constraint
128 Unique Constraint
129 Check Constraint
130 Default Constraint
131 Primary & Foreign Key Concept
132 Primary Key Constraint
133 Foreign Key Constraint
134 SQL Order of Execution
SQL Basics Questions
135 Questions Set – 1
136 Questions Set – 2
137 Questions Set – 3 (Joins)
138 Questions Set – 4 (Joins)
SQL Assignments
139 SQL Assignment 1
140 SQL Assignment 2
141 SQL Assignment 3
142 SQL Assignment 4
143 SQL Assignment 5
SQL Functions
144 Rank, Dense Rank & Row Number Window Functions – 1
145 Rank, Dense Rank & Row Number Window Functions – 2
146 Window Functions – Lead Function
147 Window Functions – Lag Function
148 ISNULL & Coalesce Functions
149 First_Value() Window Function
150 Last_Value() Window Function
Advanced SQL
151 Common Table Expressions – 1
152 Common Table Expressions – 2
153 Recursive Common Table Expressions
154 Stored Procedure in MS SQL Server
155 Views in MS SQL Server
156 Indexes in MS SQL Server
157 Clustered Index
158 Non Clustered Index
SQL Important Interview Questions
159 Nth Highest Salary
160 Reportee & Manager Question
161 Deleting Duplicates Q1
162 Deleting Duplicates Q2
Power BI Course Introduction
163 Microsoft Power BI Course Introduction
Introduction to Power BI
164 General Workflow Power BI
165 Downloading & Installing Power BI Desktop
166 Creating a Free Power BI Account
Data Visualization
167 Creating a Bar Chart
168 Creating a Column Chart
169 Creating a Pie & a Donut Chart
170 Creating a Clustered Column & Bar Chart
171 Creating a Line & Area Chart
172 Creating a Ribbon Chart
173 Creating a line & stacked column chart
174 Creating a Line & Clustered Column Chart
175 Creating a Scatter Plot
176 Creating a Bubble Map Visual
177 Creating a Table & Matrix Visual
178 Formatting Table & Matrix Visual
179 Creating a Funnel Chart
180 Gauge chart & KPI Visual
181 AI Visuals in Power BI
Power Query Editor
182 Detecting Data Types in Power BI Desktop
183 Data Profiling
184 Column Distribution Example
185 Appending Queries
186 Merge Inner Join
187 Left Outer Join
188 Right Outer Join
189 Left & Right Anti Join
190 Full Outer Join
191 Group By in Power Query Editor
192 Pivot, Unpivot & Transpose
193 Add – Transform Columns
DAX
194 DAX Lecture 1
195 DAX Lecture 2
196 DAX Lecture 3
197 DAX Lecture 4
198 DAX Lecture 5
199 DAX Lecture 6
200 Learning DAX with AI Tools
201 Rectifying Incorrect DAX Expressions with AI Tools
Power BI Project 1, Sales Data Analysis (Covers Data Modeling Concepts)
202 Business Requirements
203 Loading Data to PBI Desktop
204 Data Profiling & Data Transformations Part 1
205 Data Transformations Part 2
206 Primary & Foreign Key
207 Cardinality
208 Star Schema
209 Data Model Overview
210 Different Types of Filters in Filters Pane
211 Top Bottom 5 Products By Sales, Quantity and Profit
212 Sales Trends Over Time
213 Other Requirements
214 Requirement 4 DAX
215 Requirement 4 Edit Interactions
216 Other Remaining Requirements
217 Changing Filter Behaviour for Dimension Table Slicers
Power BI Project 2, Insurance Data Analysis
218 Downloading & Installing MSSQL Server
219 Importing Data to MSSQL Server
220 Loading Data to Power BI Desktop
221 Table View & Data Profiling
222 Adding Slicers & Text
223 Adding New Card Visuals
224 Adding a Multi Row Card & a Ribbon Chart
225 Adding a Bar & a Line Chart
226 Adding a Donut Chart & Matrix Visual
227 Publishing the Report to Power BI Service
228 Scheduling Refresh
229 Drill Through Filter
230 Testing Scheduled Refresh & Publishing the updated report
231 Creating & Testing Roles in PBI Desktop
232 Testing & Implementing RLS in Power BI Service
233 Power BI Reports & Dashboards
234 Sentiment Analysis Power Query
235 Sentiment Analysis Adding Visuals to the Report
Power BI Project 3, UPI Transactions Data Analysis
236 Loading Data into Power BI Desktop
237 Data Profiling
238 Size & Position of slicers
239 Formatting the Slicers
240 Adding a Page & Age Group Column
241 Adding a Line Chart
242 Adding a Matrix Visual
243 Syncing Slicers & Applying Conditional Formatting
244 Adding Bookmarks for Transactions
245 Adding Bookmarks for Remaining Balance
246 Publishing the Report to Power BI Service
Miscellaneous Section Power BI
247 SQL + Power BI Scenario based question – 1
248 Power BI Scenario Based Question – 2
Getting Started with Microsoft Excel
249 Home Tab Font Group
250 Home Tab Alignment Group
251 Home Tab Number Group Part 1
252 Home Tab Number Group Part 2
253 Home Tab Styles Group Conditional Formatting 1
254 Home Tab Styles Group Conditional Formatting 2
255 Draw Tab & Cell Styles
256 Excel Functions Video 1
257 Excel Functions Video 2
258 Excel Functions Video 3
259 Excel Functions Video 4
260 Excel Functions Video 5
261 Excel Functions Video 6
262 Excel Functions Video 7
263 Excel Functions Video 8
264 Excel Functions Video 9 VLookUp Function
265 Excel Functions Video 10 XLookUp Function
Excel Dashboard 1
266 Pivot Tables Lecture 1
267 Pivot Tables Lecture 2
268 Creating & Formatting the Column Chart
269 Creating & Formatting the Bar Chart
270 Creating & Formatting a Line Chart
271 Creating & Formatting an Area Chart
272 Creating & Formatting a Pie Chart
273 Creating the Dashboard
Excel Dashboard 2
274 Data Understanding & Cleansing
275 Data Transformation (Removing Data Quality Issues using VLookUp Function)
276 Adding Age Group & Production Cost Per Unit Column
277 Adding a 3D Column Chart
278 Adding a 3D Bar Chart
279 Adding a 3D Line Chart
280 Adding a 3D Pie Chart
281 Creating the Dashboard
Power Query Editor (MS Excel)
282 Data Profiling (Column Distribution)
283 Data Profiling (Column Profile & Column Quality)
284 Combining Queries
285 Inner Join Concept
286 Inner Join Example
287 Left Join Concept
288 Left Join Example
289 Right Join Concept
290 Right Join Example
291 Full Outer Join Concept
292 Full Outer Join Example
293 Left & Right Anti Join Concept
294 Right & Left Anti Join Example
295 Nulls in SQL Server & Power Query Editor
296 Appending two tables
297 Appending three tables
298 Power Query Editor Exercise 1
299 Power Query Editor Exercise 2
300 Power Query Editor Exercise 3
301 Power Query Editor Exercise 4
302 Power Query Editor Exercise 5
Excel Activity (Importing Data From SQL Server)
303 Importing Data to SQL Server
304 Importing Data to Excel From SQL Server
305 Data Understanding & Creating the Pivot Table
306 Adding Category Slicer
307 Adding Other Slicers & Formatting Slicers & Pivot Table
308 Refreshing the Report
Tableau
309 Work of a Data Analyst (Story Telling)
310 Downloading & Installing Tableau Public
311 Loading Data into Tableau Public
312 Creating Column & Bar Chart
313 Saving Your Work to Tableau Public
314 Horizontal & Vertical Axis
315 Stacked & 100% Stacked Column Chart
316 Stacked & 100 % Stacked Bar Chart
317 Creating an Area Chart
318 Creating a Line Chart
319 Creating a Scatter Plot
320 Creating Pie Chart & Tree Map
321 Creating a Donut Chart
322 Creating a Lollipop Chart
323 Filters Shelf in Tableau 1
324 Filters Shelf in Tableau 2
325 Symbol & Filled Map
326 Funnel & Packed Bubble Chart
327 Sets in Tableau
328 Parameters in Tableau
329 Sets & Parameters
Tableau Dashboard 1
330 Importing Data
331 Creating & Formatting a Bar Chart
332 Creating & Formatting a Pie Chart
333 Creating & Formatting a Line Chart
334 Creating & Formatting a Scatter Plot
335 Creating the Dashboard
Tableau Dashboard 2
336 Importing Data
337 Transactions by City
338 Number of Transactions by Age Group
339 Transactions by Payment Method & Merchant Name
340 Adding Filters
341 Creating the Dashboard
Tableau Prep Builder
342 Downloading & Installing Tableau Prep Builder
343 Understanding the Dataset
344 Connecting to Text File & Microsoft Excel
345 Removing Additional Columns
346 Cleaning Orders Central Table
347 Cleaning Orders East Table
348 Cleaning Orders West Table
349 Assigning Data Roles to Geographical Fields
350 Combining Different Tables
351 Cleaning Returns Table
352 Joining Tables
353 Cleaning Combined Table
SQL + Tableau Project (Student Depression Data Analysis)
354 Importing Data to SQL Server
355 Modifying Gender Column
356 Adding the Age Group Column
357 Column Distribution remaining columns
358 Adding Index Column & Updating depression column
359 Downloading & Installing Tableau Desktop
360 Bringing Data from SQL Server to Tableau Desktop
361 Academic Pressure & Student Count
362 Financial Stress & Student Count
363 Study Satisfaction & Student Count
364 Sleep Duration & Student Count
365 Study Hours & Student Count
366 Creating the Student Count Analysis Dashboard
367 Publishing the report to Tableau Cloud
Snowflake
368 Creating Snowflake Free Trial Account
369 Creating a SQL Worksheet
370 Snowflake Architecture
371 Setting up a Warehouse in Snowflake
372 Signing up for an AWS Account
373 Creating S3 Bucket
374 Uploading Data to Amazon S3 Bucket
375 Creating Roles using IAM
376 Creating Integration Object
377 Loading Data
378 Creating Free Azure Account
379 Creating Storage Account in Azure
380 Creating Containers in Azure & Loading Data in Containers
381 Creating Integration Object to Connect to Azure
382 Creating the stage area & loading data in table in snowflake
Connecting Snowflake to Power BI & Tableau
383 Connecting Snowflake to Power BI
384 Connecting Snowflake to Tableau
AWS + Snowflake + Power BI Project
385 Creating Amazon S3 Bucket & Loading Data into it
386 Creating the Role
387 Creating the Integration Object & Updating the Trust Policy
388 Loading Data into Snowflake
389 Understanding the Data
390 Data Transformation using Snowflake SQL
391 Adding Rainfall Groups Column
392 Importing Data into Power BI from Snowflake
393 Adding Rainfall Analysis page in the Power BI report
394 Adding Other Pages to the Power BI report
395 Publishing the report to Power BI Service
AWS + Snowflake + Tableau Project
396 Creating & Loading Data to S3 Bucket
397 Creating the Role
398 Creating the Integration Object & updating the trust policy
399 Loading Data into Snowflake
400 Data Understanding
401 Data Transformation using Snowflake SQL
402 Connecting Snowflake to Tableau
403 Creating Charts for Monthly Usage Consumption
404 Creating Charts for Cost Savings
405 Creating the Dashboard
406 Publishing the workbook to Tableau Cloud
New End to End Power BI Project 1 (Data Source – Dataflow)
407 Downloading, Installing & Configuring Standard Mode Gateway
408 Downloading & Installing Microsoft SQL Server
409 Importing Data to SQL Server
410 Creating the Dataflow using Power BI Service
411 Importing Data into Power BI Desktop from dataflow
412 Column definitions & dataset description
413 Data Types & Profiling in Power Query Editor
414 Renaming & Inserting shape on Page 1
415 Loan Amount by Purpose (DAX Used – SUMX, FILTER, NOT, ISBLANK)
416 Average Income by Employment Type (DAX Used – CALCULATE, AVERAGE & ALLEXCEPT)
417 Default Rate by Employment type(DAX – ALL,ALLEXCEPT,COUNTROWS,DIVIDE,FILTER etc)
418 Average Loan by Age Groups (DAX Used – AVERAGE, AVERAGEX & VALUES)
419 Data Validation for Average Loan by Age Groups
420 Default Rate by Year (DAX Used – CALCULATE, COUNTROWS, ALLEXCEPT, FILTER, DIVIDE)
421 Data Validation for Default Rate by Year
422 Median calculation & validation using MEDIANX DAX Function
423 Median Loan Amount by credit score category
424 Adding Donut Chart to show Average Loan Amount by Age Group & Marital Status
425 Data Validation (Donut Chart)
426 Loan(Adults) by credit categories (DAX Used – CALCULATE,AVERAGEX,SUM)
427 Total Loan (Middle Age Adults) by have Mortgage – Dependents
428 Data Validation (Clustered Column Chart)
429 Data Validation & Loans by education type
430 Creating the YOY Loan amount DAX Measure
431 Creating YOY Default Loans change DAX Measure
432 Adding Line charts to represent YOY DAX Measures
433 YTD Loan amount by credit score bins & marital status
434 Adding Decomposition Tree (DAX Used – SWITCH Function)
435 Setting up Schedule Refresh for Dataflow
436 Setting up Incremental Refresh for Dataflow
437 Publishing the report to Power BI Service & scheduling refresh for report
438 Sharing the Report
New End to End Power BI Project 2 (Datasource – MYSQL Database & SQL Server)
439 Installing MYSQL Server & MYSQL Workbench
440 Understanding the Test Environment Data & Requirements
441 Importing the data in test environment in SQL Server
442 Applying Left Join in SQL Server to prepare the data to be used for reporting
443 Importing the Data to Power BI Desktop from Test Environment
444 Creating the DAX Measures & KPIs for Page 1
445 Creating the DAX Measures & KPIs for Page 2
446 Importing Data into Production Environment in SQL Server
447 Data Cleaning using SQL & transitioning the report from test to Production
448 Downloading & Installing the MYSQL Connector
449 Importing data into MYSQL Database
450 Creating Equivalent SQL Code in MYSQL Workbench to populate New Table
451 Creating Workspace & Publishing SQL Server Data Source’s report
452 Importing Data into Power BI Desktop from MYSQL Database
453 Transitioning the report using Advanced Editor in Power Query Editor
454 Data Validation & Publishing New report to MYSQL Database Workspace
New End to End Power BI Project 3 (Datasource – Google Big Query)
455 Creating Free Google Cloud Account
456 Loading Data into Google BigQuery & connecting BigQuery to Power BI
457 Using SQL in BigQuery for Data understanding & transformations
458 Understanding & Cleaning the data using Power Query Editor
459 YOY Sales Growth (Calculate, Year, MAX, IF, BLANK DAX Functions)
460 Adding the Offer Price Column & Scatter Plot
461 Using MEDIANX DAX Function to create median sales price change by region chart 0
462 Adding Units Sold (CALCULATE, DISTINCTCOUNT, YEAR, QUARTER, MAX DAX Functions)
463 Last 12 month Sales (CALCULATE, DATESINPERIOD & SUM DAX functions)
464 Creating the Sales performance page
465 Sales by Region (CALCULATE, SUM & ALLEXCEPT DAX Function)
466 Downloading & Installing Microsoft SQL Server
467 TOTALYTD DAX Function & table visual
468 Adding the donut chart on sales performance page
469 Adding Age column & Key Influencers visual
470 Offer to SQM Price
471 Publishing the report to Power BI Service
472 Creating & Publishing the report to New Workspace
473 Adding clustered bar chart to show Avg offer – purchase price comparison
474 Adding other visuals on House type analysis & Publishing the report
New End to End Power BI Project 4 (Data Source – Azure SQL Database)
475 Creating Free Azure Account
476 Loading Data to Azure SQL Database
477 Data Cleaning using Azure SQL
478 Connecting Power BI to Azure SQL Database using ‘Database’ option in Power BI
479 Connecting to Azure SQL Database using Microsoft Account option in Power BI
480 Understanding the Data
481 Data Cleaning
482 Using DAX to create discount %, profit % & cost price column
483 Adding the Brands Overview Page
484 Adding Visuals from App Source to second report page
485 Adding Bar chart to represent top 5 brands by highest average discount %
486 Adding Donut Chart to represent top 5 brands by variety count
487 Adding a ribbon chart to represent top 5 brands by average sales price
488 Adding an Area chart to show top 5 brands by highest average profit %
489 Adding Circle graph to represent bottom 5 brands by profit% & publishing report
490 Sharing the report through Apps in Power BI Service
New Power BI Project Using AI Tools
491 Creating the data using SQL & Perplexity
492 Removing Inconsistencies from Date Column using SQL & Perplexity
493 Combining Data From Three Tables Using SQL Joins
494 Loading Data into Power BI Desktop
495 KPI, Chart and DAX recommendation using Perplexity
496 Data Cleaning
497 Cleaning Other Date Columns
498 Number of Transactions by Type
499 Transactions by Month
500 Top 2 Transactions by Name
501 Total Balance by Account Type
502 Inactive Accounts by Year & Month
503 Customer Count by Gender
504 Number of Customers by Age Group
505 Creating & Formatting the Tree Map
506 Adding Remaining Charts
507 Publishing the Report to Power BI Service
Creating GITHUB Account & uploading Power BI Projects to GITHUB Account
508 Creating the GITHUB Account
509 Uploading Power BI Project to GITHUB Account
Prompt Engineering & Generative AI For Data Analytics
510 What is AI
511 What is Generative AI – Lec+2+Twinkle+Twinkle+Video+Resource
512 What is Generative AI
513 Traditional AI Vs Gen AI
514 Evolution & Relevance
515 Learning the Basics
516 GEN AI For Practitioners & Developers
517 What is Prompt Engineering
518 Key Principles of Prompt Engineering
519 Zero, One & Few shot Prompting
520 Chain of Thoughts
521 Instruction Prompting
522 Role Based Prompting
523 Common Pitfalls
524 Ethical Prompting
525 Learning SQL Basics with the help of AI Tools (Perplexity)
526 Rectifying Incorrect SQL Query using AI Tools (Perplexity)
527 SQL Code Modification from MYSQL TO MSSQL
528 SQL Scenario based Question
529 SQL Interview Prep with AI Tools Set 1
530 SQL Interview Prep with AI Tools Set 2
531 Python Installation with Anaconda
532 Basic Python Scripts with Perplexity
533 Correcting Python scrips having errors using AI Tools (Perplexity)
534 Understanding Joins using Perplexity
535 Data Profiling using Pandas & Perplexity
536 Python Interview Prep Set 1
537 Python Interview Prep Set 2
538 Mini Python Insurance Project using Perplexity
539 Mini Python Banking Project using Perplexity
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