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Udemy – Data Analytics Masters – From Basics To Advanced 2025-3
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Course content
Sections:
11
•
Activities:
1
•
Resources:
260
- Announcements
- 3 What is Data Analytics
- 4 Importance of Data Analytics
- 5 Types of Data
- 6 Types of Statistical Analysis
- 7 Steps to obtain a Data Analytics solution
- 8 Business Understanding
- 9 Data Understanding
- 10 Data Collection
- 11 Data Preparation
- 12 Data Modelling
- 13 Deployment
- 14 Use Case
- 2 Lets install Python together
- 3 Google Colab whats that
- 4 Lets get familiar with chatGPT
- 5 Introduction to Python
- 6 Variables Keywords
- 7 Datatypes Operators
- 8 Lists
- 9 Tuples
- 10 Sets
- 11 Dictionary
- 12 Loops Iteration
- 13 Functions
- 14 Map Reduce Filter
- 15 File Handling
- 16 Control Structures
- 17 OOPS
- 18 NumPy
- 19 Pandas
- 20 Data Visualization
- 21 Matplotlib
- 22 Seaborn
- 2 Introduction
- 3 Types of Data Agenda
- 4 Descriptive Stats
- 5 Inferential Stats
- 6 Qualitative Data
- 7 Quantitative Data
- 8 Sampling Techniques Agenda
- 9 Population vs Sample
- 10 Why Sampling is important
- 11 Types of Sampling
- 12 Cluster Random Sampling
- 13 Probability Sampling
- 14 Non probability sampling
- 15 Population Sampling
- 16 Why n 1 and not n
- 17 Descriptive Analytics Agenda
- 18 Measures of Central Tendency
- 19 Mean
- 20 Median
- 21 Mode
- 22 Measures of Dispersion
- 23 Range
- 24 IQR
- 25 Variance Standard Deviation
- 26 Mean Deviation
- 27 Probability Agenda
- 28 Probability
- 29 Addition Rule
- 30 Independent Events
- 31 Cumulative Probability
- 32 Conditional Probability
- 33 Bayes Theorem 1
- 34 Bayes Theorem 2
- 35 Probability Distrubution Agenda
- 36 Uniform Distribution
- 37 Binomial Distribution
- 38 Poisson Distribution
- 39 Normal Distribution Part 1
- 40 Normal Distribution Part 2
- 41 Skewness
- 42 Kurtosis
- 43 Calculating Probability with Z score for Normal Distribution Part 1
- 44 Calculating Probability with Z score for Normal Distribution Part 2
- 45 Calculating Probability with Z score for Normal Distribution Part 3
- 46 Covariance Correlation Agenda
- 47 Covariance
- 48 Correlation
- 49 Covariance VS Correlation
- 50 Hypothesis Testing
- 51 Tailed Tests
- 52 p value
- 53 Types of Test
- 54 T Test
- 55 Z Test
- 56 ANOVA
- 57 Chi Square Test
- 58 Correlation Test Practicals
- 2 Agenda
- 3 DADS Process
- 4 What is EDA
- 5 Visualization
- 6 Steps involved in EDA Data Sourcing
- 7 Steps involved in EDA Data Cleaning
- 8 Handle Missing Values Theory
- 9 Handle Missing Values Practicals
- 10 Feature Scaling Theory
- 11 Standardization Example
- 12 Normalization Example
- 13 Feature Scaling Practicals
- 14 Outlier Treatment Theory
- 15 Outlier Treatment Practicals
- 16 Invalid Data
- 17 Types of Data
- 18 Types of Analysis
- 19 Univariate Analysis
- 20 Bivariate Analysis
- 21 Multivariate Analysis
- 22 Numerical Analysis
- 23 Analysis Practicals
- 24 Derived Metrics
- 25 Feature Binning Theory
- 26 Feature Binning Practicals
- 27 Feature Encoding Theory
- 28 Feature Encoding Practicals
- 29 Case Study
- 30 Data Exploration
- 31 Data Cleaning
- 32 Univariate Analysis
- 33 Bivariate Analysis Part 1
- 34 Bivariate Analysis Part 2
- 35 EDA Report
- 2 Installation
- 3 Data Architecture File server vs client server
- 4 Introduction to SQL
- 5 Constraints in SQL
- 6 Table Basics DDLs
- 7 Table Basics DQLs
- 8 Table Basics DMLs
- 9 Joins
- 10 Data Import Export
- 11 Aggregation Functions
- 12 String functions
- 13 Date Time Functions
- 14 Regular Expressions
- 15 Nested Queries
- 16 Views
- 17 Stored Procedures
- 18 Windows Function
- 19 SQL Python connectivity
- 2 Pre defined Functions
- 3 Datetime Functions
- 4 String Functions
- 5 Mathematical Functions
- 6 Lookup HlookupVlookup
- 7 Logical Error Functions
- 8 Statistical Functions
- 9 Images in Excel
- 10 Excel Formatting
- 11 Custom Formatting
- 12 Conditional Formatting
- 13 Charts in Excel
- 14 Data Analysis using Excel
- 15 Pivot Tables
- 16 Dashboarding in Excel
- 17 Others
- 18 What If Tools Scenario Manager Goal Seek
- 2 Introduction
- 3 Life Hack How to have Power BI Pro License
- 4 Power BI Desktop
- 5 Power BI Services
- 6 Power Query Editor
- 7 Data Profiling
- 8 Group by Dialog
- 9 Applied Steps
- 10 Append vs Merge
- 11 Power BI Visuals
- 12 Power BI Charts
- 13 Introduction to DAX
- 14 Implicit Measures
- 15 DAX Formula
- 16 Basic DAX Functions
- 17 Date Functions
- 18 CALENDAR Functions
- 19 Contexts Row vs Filter
- 20 CALCULATE FILTER
- 21 IF ELSE Conditions
- 22 Time Intelligence Functions
- 23 X vs Non X Functions
- 24 Tool Tips Drill Throughs
- 25 Power BI Relationships
- 26 KPIs in Power BI
- 27 Administration in Power BI
- 28 Static Row Level Security
- 29 Dynamic Row Level Security
- 30 Dataflows in Power BI
- 31 Formatting
- 32 Best Practices
- 33 EDA
- 34 Live Projects
- 2 What is Data Visualization
- 3 BI Process
- 4 What is Tableau
- 5 Features of Tableau
- 6 How to use Tableau
- 7 Tableau Architecture
- 8 Tableau Desktop
- 9 Tableau vs Power BI
- 10 Relationships Joins Unions
- 11 Sets in Tableau
- 12 Groups in Tableau
- 13 Hierarchies in Tableau
- 14 Filters in Tableau
- 15 Highlighting
- 16 Device Deisgner
- 17 Parameters
- 18 Data Blending
- 19 Transparency
- 20 Date Aggregation
- 21 Generated Fields
- 22 Discrete vs Continuous
- 23 Charts in Tableau
- 24 Pivot Tables in Tableau
- 25 LOD Expressions
- 26 Calculated Fields
- 27 Formatting
- 28 Forecasting in Tableau
- 29 Analytics in Tableau
- 30 Dashboarding
- 2 Introduction
- 3 Predictive Analytics Process
- 4 How model works
- 5 Why Predictive Analytics
- 6 Applications
- 7 What is Machine Learning
- 8 Types Of Machine Learning
- 9 Classification
- 10 KNN
- 11 KNN Excel example
- 12 Classification Practical
- 13 KNN Code
- 14 Decision Tree Example
- 15 Decision Tree Code
- 16 Random Forest
- 17 Random Forest Code
- 18 Boosting
- 19 Boosting Code
- 20 Regression Theory
- 21 Regression Practicals
- 22 Clustering
- 23 Clustering Practicals
- 24 Time Series
- 25 Time Series Forecasting Code
- 2 Introduction
- 3 What is ETL
- 4 ETL Tools
- 5 What is Data Warehouse
- 6 Benefits of Data Warehouse
- 7 Data Warehouse Structure
- 8 Why do we need Staging
- 9 What are Data Marts
- 10 Data Lake
- 11 Data lake vs Data Warehouse
- 12 Elements of Data lake
- 1 Welcome
- 2 Churn Analysis Power BI
- 3 Banking Risk Analysis Power BI Part 1
- 4 Banking Risk Analysis Power BI Part 2