Basic arithmetic operations

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Logical functions (IF, AND, OR, NOT)

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Text functions

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CONCATENATE, LEFT, RIGHT, MID

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Date and time functions

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TODAY, NOW, DATEDIF

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Lookup functions

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VLOOKUP, HLOOKUP, INDEX, MATCH

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Statistical functions

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AVERAGE, MEDIAN, MODE, STDEV

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Removing duplicates

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Handling missing data

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Text to Columns

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Find and replace

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TRIM, CLEAN, SUBSTITUTE functions

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PivotTables and Pivot Charts

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Data tables

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Conditional formatting

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What-If Analysis

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Goal Seek, Data Tables, Scenario Manager

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Creating and customizing charts

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Bar, line, pie, scatter

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Sparklines

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Heat maps

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Creating dashboards

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Array formulas

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Advanced lookup (XLOOKUP)

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SUMIFS, COUNTIFS

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Data transformation

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Merging and appending queries

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Advanced data manipulation

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Creating data models

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Using DAX (Data Analysis Expressions) for advanced calculations

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Recording and running macros

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Basic VBA scripting for automation

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Protecting worksheets and workbooks

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Sharing and tracking changes

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Using Excel online and collaborative features

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Password protection

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Encrypting workbooks

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Using secure connections for data sources

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Connecting Excel with databases (SQL)

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Importing data from external sources (APIs, web scraping)

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Using Excel with BI tools (Power BI, Tableau)

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Basic SQL Queries

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SELECT statements

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Filtering data with WHERE clause

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Sorting data with ORDER BY

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DISTINCT keyword

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LIMIT clause

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Aliases (AS keyword)

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Aggregations and Grouping

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COUNT, SUM, AVG, MIN, MAX functions

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GROUP BY clause

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HAVING clause

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Joins

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INNER JOIN

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LEFT JOIN (or LEFT OUTER JOIN)

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RIGHT JOIN (or RIGHT OUTER JOIN)

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FULL JOIN (or FULL OUTER JOIN)

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CROSS JOIN

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SELF JOIN

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Subqueries

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Inline subqueries

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Correlated subqueries

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EXISTS and NOT EXISTS

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Set Operations

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UNION and UNION ALL

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INTERSECT

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EXCEPT (or MINUS in some databases)

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Data Manipulation

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INSERT statements

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UPDATE statements

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DELETE statements

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String functions

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CONCAT, SUBSTRING, REPLACE

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Date and time functions

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NOW, DATEADD, DATEDIFF

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Numeric functions

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ROUND, CEIL, FLOOR

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OVER clause

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ROW_NUMBER(), RANK(), DENSE_RANK()

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LEAD() and LAG()

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Creating and using indexes

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Understanding query execution plans

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Optimizing queries for performance

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Understanding primary keys and foreign keys

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Normal forms (1NF, 2NF, 3NF)

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Designing relational database schemas

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Creating and using views

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Updating data through views (when possible)

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Creating and using stored procedures

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Creating and using user-defined functions

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Understanding the differences and use cases

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BEGIN, COMMIT, and ROLLBACK

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Understanding ACID properties

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Managing transaction isolation levels

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Managing user permissions and roles

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Using GRANT and REVOKE statements

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Understanding database security best practices

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Common Table Expressions (CTEs)

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Recursive queries

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Pivoting and unpivoting data

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Connecting SQL with BI tools (Power BI, Tableau)

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Using SQL in combination with programming languages (Python, R)

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Descriptive Statistics

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Measures of central tendency (mean, median, mode)

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Measures of dispersion

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Range, variance, standard deviation, interquartile range

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Measures of shape (skewness, kurtosis)

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Data visualisation techniques

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Histograms, box plots, bar charts

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Basic probability concepts

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Independent and dependent events, conditional probability

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Probability distributions

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Normal, binomial, Poisson, exponential

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Probability density function (PDF)

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Cumulative distribution function (CDF)

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Law of large numbers and central limit theorem

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Population vs. sample

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Sampling methods (random, stratified, cluster)

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Sampling distributions

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Estimation (point estimates, confidence intervals)

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Null and alternative hypotheses

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Type I and Type II errors

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P-values and significance levels

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Common tests

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T-test, chi-square test, ANOVA, z-test

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One-tailed vs. two-tailed tests

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Pearson and Spearman correlation coefficients

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Simple linear regression

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Multiple linear regression

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Assessing model fit (R-squared, adjusted R-squared)

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Residual analysis

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One-way ANOVA

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Two-way ANOVA

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Assumptions and interpretation of results

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Mann-Whitney U test

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Wilcoxon signed-rank test

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Kruskal-Wallis test

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Chi-square test of independence

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Components of time series

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Trend, seasonality, cycle, irregular

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Moving averages and exponential smoothing

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Autocorrelation and partial autocorrelation functions

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ARIMA models (Auto-Regressive Integrated Moving Average)

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Bayesian theorem

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Prior, likelihood, and posterior distributions

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Bayesian inference and credibility intervals

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Principal component analysis (PCA)

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Factor analysis

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Cluster analysis

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Discriminant analysis

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Control charts (X-bar, R-chart, p-chart)

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Process capability analysis

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Principles of experimental design

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Randomization, replication, blocking

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Completely randomized design

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Randomized block design

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Factorial design

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Kaplan-Meier estimator

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Cox proportional hazards model

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Hazard functions and survival functions

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Understanding the ethical considerations in data analysis

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Avoiding common pitfalls and biases

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Ensuring transparency and reproducibility of results

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Getting Started with Power BI

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Understanding Power BI Desktop, Power BI Service, and Power BI Mobile

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Understanding Power BI Desktop, Power BI Service, and Power BI Mobile

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Basic navigation and interface of Power BI Desktop

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Data cleaning and transformation using Power Query Editor

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Merging and appending queries

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Data types and error handling

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Creating relationships between tables

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Understanding and using star and snowflake schemas

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Managing relationships (one-to-one, one-to-many, many-to-many)

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Using calculated columns and tables

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Basics of DAX syntax and functions

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Creating calculated columns and measures

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Understanding row context and filter context

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Common DAX functions (SUM, COUNT, AVERAGE, MIN, MAX)

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Time intelligence functions (DATEADD, DATESYTD, SAMEPERIODLASTYEAR)

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Advanced DAX functions (CALCULATE, ALL, FILTER, RELATED)

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Creating and customizing basic charts (bar, line, pie, scatter, etc.)

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Using slicers for filtering data

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Creating and customizing tables and matrices

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Using maps and geographical data visualizations

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Custom visualizations from the marketplace

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Using bookmarks and selections for interactive reports

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Creating drill-through and drill-down reports

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Implementing conditional formatting

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Designing report layouts and themes

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Creating and managing dashboards in Power BI Service

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Pinning visuals to dashboards

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Using Q&A feature for natural language queries

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Publishing reports to Power BI Service

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Understanding workspaces, apps, and content packs

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Managing datasets and data refresh schedules

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Sharing reports and dashboards with stakeholders

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Collaborating with team members

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Integrating Power BI reports into applications

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Using Power BI REST API for automation

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Implementing row-level security (RLS)

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Managing roles and permissions

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Understanding and applying data protection and compliance measures

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Optimizing data models for performance

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Using the Performance Analyzer tool

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Best practices for efficient report design

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Using AI visuals (Key Influencers, Decomposition Tree, Q&A Visual)

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Integrating R and Python scripts in Power BI

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Implementing what-if parameters for scenario analysis

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Connecting Power BI with other Microsoft services (Excel, Azure, SQL Server)

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Integrating with third-party tools and data sources

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Using Power Automate for workflow automation

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Managing Power BI gateway for on-premises data sources

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Monitoring usage and performance

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Implementing governance and best practices for organization-wide usage

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Participating in Power BI community forums and events

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Utilizing Power BI documentation and learning resources

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Staying updated with new features and updates

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Basic Python Programming

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Syntax and semantics

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Data types (integers, floats, strings, lists, tuples, dictionaries, sets)

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Control structures (if statements, for and while loops)

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Functions and lambda expressions

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List comprehensions and generator expressions

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Creating and manipulating DataFrames and Series

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Importing and exporting data (CSV, Excel, SQL, JSON)

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Data cleaning (handling missing values, duplicates, data type conversions)

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Data transformation (merging, joining, concatenating, pivoting)

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GroupBy operations

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Time series analysis

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Creating and manipulating arrays

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Array operations and broadcasting

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Mathematical functions and linear algebra

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Working with random data and statistical functions

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Plotting with Matplotlib

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Creating and customizing plots (line, bar, scatter, histogram, boxplot, etc.)

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Advanced visualization with Seaborn

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Plotting geospatial data with Folium and GeoPandas

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Descriptive statistics (mean, median, mode, variance, standard deviation)

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Probability distributions

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Hypothesis testing

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Correlation and regression analysis

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Connecting to SQL databases using SQLAlchemy

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Executing SQL queries from Python

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Using Pandas to read from and write to SQL databases

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Fetching web pages with requests

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Parsing HTML with BeautifulSoup

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Navigating and extracting data from websites

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Handling dynamic content with Selenium

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Understanding the basics of machine learning

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Types of machine learning (supervised, unsupervised, reinforcement)

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Key concepts (features, labels, training, testing, validation)

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Handling missing values

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Feature scaling (normalisation, standardisation)

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Encoding categorical variables

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Splitting data into training and testing sets

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Regression

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Linear regression

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Polynomial regression

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Ridge and Lasso regression

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Classification

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Logistic regression

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K-Nearest Neighbors (KNN)

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Decision Trees and Random Forests

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Support Vector Machines (SVM)

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Naive Bayes

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Clustering

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K-Means Clustering

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Hierarchical Clustering

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DBSCAN

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Dimensionality Reduction

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Principal Component Analysis (PCA)

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t-SNE

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Understanding overfitting and underfitting

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Cross-validation techniques

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Metrics for regression (MSE, RMSE, R-squared)

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Metrics for classification (accuracy, precision, recall, F1 score, ROC-AUC)

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Introduction to model deployment strategies

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Saving and loading models

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Basics of deploying models using Flask or FastAPI or Streamlit

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Basics of neural networks

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Understanding layers, neurons, and activation functions

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Deep learning frameworks (TensorFlow, PyTorch)

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