Books Summary:

• Neville Goddard, Joseph Murphy & Florence Scovel Shinn
• Legado de Epicteto, Séneca y Marco Aurelio
• Obra Completa – Robert Greene (Top 10 Topics)
• Hábitos, Presencia, Grit, Kaizen, Sentido (5 Books)
• Libros Conciencia Cuántica (6 Books)
• El Protocolo del Espejo Cuántico
• El Código Fuente del Universo
• El Último Libro Prohibido de Hermes
• Las Seis Claves del Éxito
• Visualización Creativa, Coherencia Cuántica, Inteligencia Emocional y Genotipos
• Silencio • Palabra • Flow — Manual Práctico
• Cloud Outage Report
• Formato Descuentos Locales · jobaqui.com
• Descuentos Locales Verificados · jobaqui.com
• 20 Essential Books by Carl G. Jung
• Machiavelli Applied: 30 Foundations of Power, Strategy, and Mastery
• The 10 books that best explain seduction, dating, and human connection in the age of social media

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Applications:

• Daily Practical Guide (Neville Goddard – Joseph Murphy – Florence Scovel Shinn)
• Aplicación Práctica del Legado Estoico
• Manual Bilingue 10 Pilares Quanticos
• Manual Psicotrónico Interactivo
• Plan Integral para Optimizar la Red de Mielina Cuántica
• Técnicas cuánticas aplicadas al cerebro
• 7 Protocolos + 5 Señales Quanticas
• Persuasión · Seducción · Manipulación
• Manual Mental
• Modelo Estructurado del Exito
• Manual del Observador
• Chopra ↔ Kybalion — Manual Práctico
• Modelo de Medición del Exito — 5 Claves
• Guía práctica 2025 — 7 Hábitos & 4 Acuerdos
• Afirmaciones – Decretos – Plegaria Cuántica – Oración Científica – Ritual
• Del Gobierno de las Pasiones a la Transmutación de Energías
• Balance Energético — Estoico & Hermético
• Quantum Vibration Calculator
• Termómetro Detallado de Estado de Ánimo
• Inteligencia Emocional y Temperamentos
• Alineación con la Actualidad
• El Secreto Prohibido de los Esenios
• ADN divino
• Chakras
• Estados Alterados & Telepatía
• Epigenética & Biología Cuántica
• Frecuencias — Guía práctica
• Evolución Interna del Ser
• Análisis Cuántico Total — Nivel Científico-Esotérico
• El Código Universal de la Conciencia Antigua
• Mónada Geoglífica
• Conciencia Cuántica
• La Llave Maestra
• Lógica Inductiva vs Inteligencia Intuitiva
• Plan de Cierre 2025
• Conciencia Unificada
• Frecuencias Cuánticas — Del Buscador al Emisor Consciente
• Modelo del Bosque Cuántico Universal
• Google’s Quantum Chip Just Broke Physics
• Entrelazamiento Cuántico y Manifestación
• The Quantum Soul — 20 Analytical Topics
• The Quantum Mental Field — 8 Bridges between Science & Spirit
• AI 2026 · VISIÓN GLOBAL & AI ENGINEER
• Parallels between Quantum Biology and Artificial Intelligence
• Las 8 Fases de la Visualización Creativa Elevada
• Introducción — El Sello Roto (ES)
• Introduction — The Broken Seal (EN)
• Gemini 3 Pro en el Tablero Global de la IA
• Advances in AI, quantum computing, and biotechnology
• Quantum Mind and Primal Consciousness
• Cloudflare Case 2025 — Autopsy of a Global Internet Outage
• Threat Landscape & Defense Strategy Against Autonomous AI Attacks
• Estado de amenaza y defensa ante ataques autónomos con IA
• Integral Framework for Next-Generation Assisted Intelligence
• Marco Integral para la Inteligencia Asistida de Próxima Generación
• AI Model Landscape: From Classic Machine Learning to the Cognitive Systems of the Future
• Modelos de Inteligencia Artificial: Del Machine Learning Clásico a los Sistemas Cognitivos del Futuro
• Mapa Interactivo de Conciencia Predictiva
• Manual de Conciencia Predictiva
• Mantra, Propósito y Rituales Personales
• New forms of information storage
• Subtle forces · Inner field
• 15 Current Frontiers in Brain Research
• 15 Líneas Actuales de Investigación del Cerebro
• Scientific Frontiers & Nobel Highlights 2025
• Premios y Fronteras Científicas 2025
• Frontier Research Transforming Human Reality
• Investigaciones que Cambiarán la Realidad Humana
• 17 Technology Trends for 2026
• 17 Tendencias Tecnológicas 2026
• The 10 Psychological Forces that Shape Identity
• Mind, Field, and Magnetism
• Mente, Campo y Magnetismo
• Existential Gratitude
• AGEC — Scientific-Speculative 10-Level Model
• AGEC — Modelo Científico-Especulativo de 10 Niveles
• Cognitive Framework 2026
• Framework Cognitivo 2026
• GPT-5.2 — Why the Rules of AI Changed
• Rainier — Why the GPU Myth Is Ending
• Enhancing States of High Creative Coherence (HCCS)
• Potenciación de Estados de Alta Coherencia Creativa (EACC)
• Los 10 Principios Espirituales del Éxito — Deepak Chopra
• Visualization, Assumption, and Manifestation: a structural model to train the mind
• The Second Quantum Revolution: measuring the invisible and moving beyond GPS
• From a single “AI center” to an ecosystem: how power reorganizes in 2026
• Fungi That Change the Rules of the Game
• AI Agents in Education: 7 Strategic Points
• The Next Frontier: Technological Risks in AI Optical Infrastructure
• How to Talk to AI and Get Outstanding Results
• 35 Topics of a bio-digital civilization
• The 30 Signals of Digital Truth — Part I
• The 30 Signals of Digital Truth — Part II
• The 30 Signals of Digital Truth — Part III
• Computational Neuroscience
• AI is no longer the future
• Docker AI Projects Locally
• Build Local AI Agents
• Rethinking Consciousness: Are We Approaching a New Scientific Paradigm?
• The new generation of AI implementers for government
• Amazon’s “Slowdown”: Why AI Efficiency Does Not Replace Human Judgment
• AI Will Rewrite Humanity in 5 Years
• The Hierarchy of Intelligence: Who Thinks, Who Rules, and Who Masters the Self
• 12 small behaviors that reveal authentic elegance
• The Mythos Dilemma: why the world’s most powerful AI has been “locked away”
• Florence Scovel Shinn and the Invisible Game of Reality
• DeepMind, Demis Hassabis, and the new age of intelligence: 25 keys that foreshadow the redesign of the future
• The Emerald Tablets of Thoth: Atlantis, Amenti, Universal Laws, and the Return to the Source
• The Book of Enoch: Fallen Angels, Forbidden Knowledge, and the Judgment That Changed the Spiritual History of the World
• April 2026: The month OpenAI stopped looking like an app and started looking like a cognitive infrastructure
• Google Quantum AI and the Mirror of Tomorrow: When Quantum Computing Touches the Frontier of Time
• The Chinese Quantum “David”: A Molecule Against the Giants of Artificial Intelligence
• GPT 5.5: The New Era of Autonomous Agents
• DeepSeek v4: efficiency, technological sovereignty and the new cost war in artificial intelligence
• The Code of Inner Dominion
• Physical AI: when artificial intelligence leaves the screen and begins to move the world
• AI Is NOT a Bubble: It Is the New Economic Infrastructure of the 21st Century
• Quantum Computing 2026–2027: the invisible infrastructure that may redefine security, AI, and economic power
• Intel 18A: The Return of a Giant and the New War for Silicon Sovereignty
• Don’t Wait for Retirement to Start Living
• IBM breaks a frontier: when quantum simulation begins to look inside life itself
• Organic Computing: When Life Begins to Become Hardware
• AI Is Not Getting Dumber: It Is Getting More Expensive
• The Secret of Concentration: 10 Keys to Mastering Focus
• Lateral Thinking: the art of breaking mental molds to see invisible solutions
• Dangerously unstoppable: 20 laws to defeat laziness, hack discipline, and rebuild your identity
• Hacking Your Brain — Chapter 1: 15 keys to understand and hack your brain
• Hacking Your Brain — Chapter 2: the mind as relational software
• Hacking Your Brain — Chapter 3: we are contextual animals
• The Art of Personal Strategy: 20 Principles to Govern the Mind and Execute with Clarity
• Become So Calm That No One Can Manipulate You
• Money Is Energy: 20 Principles to Reprogram Your Relationship with Abundance
• Master Guide: 15 Skills for the Irreplaceable Professional (2026–2027)
• Predictive AI vs Generative AI: two intelligences, two different missions
• Emergence World Experiment
• 14 Laws of Reverse Psychology in Communication
• The universe responds when life becomes aligned
• Forbidden Metaphysics
• Proverbs as a Modern Operating System
• 6 Profitable AI Business Ideas for 2026
• The 48 Laws of Power Applied to Desire
• 6 Profitable AI Business Ideas for 2026
• Automating the “Filter, Copy, Paste, and Verify” Process
• 100_habits_emotional_mastery_module_1
• 100_habits_emotional_mastery_module_2
• 100_habits_emotional_mastery_module_3
• 100_habits_emotional_mastery_module_4
• 100_habits_emotional_mastery_module_5
• The Dark Side of the Mind
• The Art of Strategy
• The Incredible Power of Imagination
• The Magic of Faith
• The Magical Path of Intuition
• The Night Practice of Inner Change
• Use AI for Free or Pay for It Twice
• How to Think About the Future
• Human Operating System Article Training
• When AI Agents Start Coordinating: Autonomy, Cybersecurity, and the New Control Problem
• The Ladder of Consciousness
• The Adaptive Professional in the AI Era

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Nested Mind – Book Project Chapters:

• 1.- Nested Learning: The Birth of Living Artificial Intelligence
• 2.- The Subconscious as the Engine of Intelligence
• 3.- The Emotional System: Affective Intelligence as an Evolutionary Engine
• 4.- Quantum-Operational Mind: Superposition, Possibility & Decision
• 5.- How the Mind Constructs Reality: Prediction, Narrative, and Meaning
• 6.- The Self as Interface: Identity, Ego, and Self in the Architecture of Mind
• 7.- The Collective Mind and Fields of Meaning
• 8.- Architecture of Mental Time: Memory, Future, and Destiny
• 9.- Intuition, Insight, and Quantum Leap Moments
• 10.- Cognitive Mastery: How to Redesign Your Self from Within

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Data Properties – Book Project Chapters:

• Data Properties — Structural, Dynamic, Relational, Causal & Quantum Dimensions
• Propiedades de los Datos — Dimensión Estructural, Dinámica, Relacional, Causal y Cuántica

Structural Properties:

• Consitency (EN/ES).
  • Consistency — Semantic Stability in the Tabular Engine
  • Consistency — Estabilidad Semántica en el Motor Tabular
• Quality (EN/ES).
  • Quality — Purity, Accuracy and Fidelity of Data in the Tabular Model
  • Quality — Pureza, Exactitud y Fidelidad del Dato en el Modelo Tabular
• Equivalence (EN/ES).
  • Equivalence — The Ability of Data to Preserve Identity Under Multiple Representations
  • Equivalence — La Capacidad del Dato de Mantener Identidad Bajo Representaciones Distintas
• Semantic Elasticity (EN/ES).
  • Semantic Elasticity – Adaptability of meaning without loss of coherence
  • Semantic Elasticity – Adaptabilidad del significado sin pérdida de coherencia
• Integrability (EN/ES).
  • Integrability – Model Connectivity and Coexistence Capability
  • Integrabilidad – Capacidad de Conexión y Coexistencia del Modelo
• Informational Scarcity (EN/ES).
  • Informational Scarcity – Discipline of Relevant Data
  • Escasez Informacional – Disciplina del Dato Relevante
• Abstraction (EN/ES).
  • Abstraction – Separation Between Meaning and Implementation
  • Abstracción – Separación entre Significado y Implementación
• Persistence (EN/ES).
  • Persistence – Continuity of Meaning Over Time
  • Persistencia – Continuidad del Significado en el Tiempo
• Coherence (EN/ES).
  • Coherence – Logical Alignment of the Analytical Model
  • Coherencia – Alineación Lógica del Modelo Analítico
• Congruence (EN/ES).
  • Congruence – Alignment Between Intent, Model, and Outcome
  • Congruencia – Alineación entre Intención, Modelo y Resultado

Dynamic Properties:

• Frequency (EN/ES).
  • Frequency – Update Rhythm and Analytical Resonance
  • Frecuencia – Ritmo de Actualización y Resonancia Analítica
• Opportunity (EN/ES).
  • Opportunity – Temporal Window for Decision and Analytic Action
  • Oportunidad – Ventana Temporal de Decisión y Acción Analítica
• Fluency (EN/ES).
  • Fluency – Operational and Cognitive Continuity of the Analytical Model
  • Fluidez – Continuidad Operativa y Cognitiva del Modelo Analítico
• Plasticity (EN/ES).
  • Plasticity – Structural Adaptation Capacity of the Analytical Model
  • Plasticidad – Capacidad de Adaptación Estructural del Modelo Analítico
• Semantic Latency (EN/ES).
  • Semantic Latency – Temporal Gap Between Data and Analytical Understanding
  • Latencia Semántica – Desfase Temporal entre el Dato y su Comprensión Analítica
• Transmissibility (EN/ES).
  • Transmissibility – Analytical Model Capacity to Transfer Meaning Without Loss
  • Transmisibilidad – Capacidad del Modelo Analítico para Transferir Significado sin Pérdida
• Entropy (EN/ES).
  • Entropy – Natural Tendency of the Analytical Model Toward Loss of Order and Meaning
  • Entropía – Tendencia Natural del Modelo Analítico a la Pérdida de Orden y Significado

Relational Properties:

• Resonance (EN/ES).
  • Resonance – Alignment Between the Analytical Model and the User’s Natural Way of Thinking
  • Resonancia – Alineación entre el Modelo Analítico y la Forma Natural de Pensar del Usuario
• Connectivity (EN/ES).
  • Connectivity – Capacity of the Analytical Model to Integrate, Relate, and Scale Within a Data Ecosystem
  • Conectividad – Capacidad del Modelo Analítico para Integrarse, Relacionarse y Escalar en un Ecosistema de Datos
• Semantic Alignment (EN/ES).
  • Semantic Alignment – Coherence of Analytical Meaning Across the Entire Data Model
  • Alineación Semántica – Coherencia del Significado Analítico a lo Largo de Todo el Modelo de Datos
• Contextual Compatibility (EN/ES).
  • Contextual Compatibility – Capacity of the Analytical Model to Preserve Meaning Across Multiple Contexts of Use
  • Compatibilidad Contextual – Capacidad del Modelo Analítico para Mantener Sentido Bajo Múltiples Contextos de Uso
• Informational Density (EN/ES).
  • Informational Density – Relationship Between Information Quantity and Effective Analytical Value
  • Densidad Informacional – Relación entre Cantidad de Información y Valor Analítico Efectivo
• Polarity (EN/ES).
  • Polarity – Ability of the Analytical Model to Express Meaningful Tensions, Extremes, and Contrasts
  • Polaridad – Capacidad del Modelo Analítico para Expresar Tensiones, Extremos y Contrastes Significativos

Causal Properties:

• Impact (ES/EN).
  • 24. Impact – From information to action Impact is the ultimate test of the value of data: not what it describes, but what it causes when it’s used.
• Implication (ES / EN).
  • 25. Implication – Implication is the data property that determines how much a person, team, or organization feels directly involved, responsible, or challenged by the information presented.
• Consequence (ES / EN).
  • 26. Consequence – Consequence is the data property that expresses the real, derived, and sustained effects produced by decisions made based on information.
• Sensitivity (ES / EN).
  • 27. Sensitivity – Sensitivity is the data property that determines how capable data is of detecting, reflecting, and responding to relevant variations within a system, even when changes are subtle, gradual, or emergent.
• Weight (ES / EN).
  • 28. Weight – Weight is the data property that determines how much real influence information exerts within a decision-making process, regardless of its volume, frequency, or visibility.

Projective Properties:

• Inference (ES/EN).
  • 29. Inference – Inference is the data property that allows extracting conclusions, hypotheses, or non-explicit implications from available information, connecting patterns, relationships, and contexts.
• Extrapolation (ES/EN).
  • 30. Extrapolation – Extrapolation is the data property that allows projecting behaviors, outcomes, or scenarios beyond the observed range, using existing patterns, identified trends, and explicit assumptions.
• Prediction (ES/EN).
  • 31. Prediction – Prediction is the data property that allows estimating future outcomes based on models, historical patterns, and explicit assumptions, incorporating uncertainty and probability.
• Trend Potential (Tendentiality) (ES/EN).
  • 32. Trend Potential – Trend Potential is the data property that allows estimating the capacity of a signal, pattern, or behavior to become a trend, considering its direction, persistence, and expansion conditions.
• Volatility (ES/EN).
  • 33. Volatility – Volatility is the data property that describes the degree and speed at which a variable changes over time, reflecting instability, fluctuation, or significant variability.

Validation Properties:

• Replicability (ES/EN).
  • 34. Replicability – Replicability is the data property that allows a result, analysis, or conclusion to be reproduced consistently when the same conditions, methods, and assumptions are applied.
• Stability (ES/EN).
  • 35. Stability – Stability is the data property that reflects a system’s capacity to maintain coherent behaviors, relationships, and results over time, even in the presence of moderate disturbances.
• Falsifiability (ES/EN).
  • 36. Falsifiability – Falsifiability is the property of data, models, and conclusions that allows them to be refuted through empirical evidence when new observations contradict assumptions or expected results.
• Reliability (ES/EN).
  • 37. Reliability – Reliability is the property of data, systems, and analyses that expresses the degree to which results can be safely used for decision-making, consistently and predictably over time.

Quantum Properties:

• Data Auric Field (ES/EN).
  • 38. Data Auric Field – The Data Auric Field is the property that describes the contextual, perceptual, and relational influence that a dataset exerts beyond its explicit content, affecting interpretation, trust, decisions, and human behavior.
• Informational Superposition (ES/EN).
  • 39. Informational Superposition – Informational Superposition is the data property that describes the simultaneous coexistence of multiple interpretations, states, and possible meanings within the same dataset, before a reading, decision, or action collapses them into a concrete narrative.
• Semantic Entanglement (ES/EN).
  • 40. Semantic Entanglement – Semantic Entanglement is the data property that describes the deep interdependence between meanings, contexts, and decisions, where the interpretation of a data point cannot be fully separated from other data, narratives, systems, and observers.
• Field Coherence (ES/EN).
  • 41. Field Coherence – Field Coherence is the data property that expresses the degree of harmonic alignment between information, interpretation, decision, and action within a system, so that data is not only correct, but consistent with each other and with the reality they aim to represent.

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Training:

• Plan de 4 Semanas · Desde Cero
• Domina ChatGPT-5
• Excel – Limpieza & Transformación de Datos · Taller 4h
• Continuing Education — Proyección estratégica
• Real & Free Datasets to Practice Excel, Power BI & AI (EN)
• Datasets reales y gratuitos para practicar Excel, Power BI e IA (ES)
• 15 capacidades clave de SQL Server 2025 con aplicaciones prácticas (ES/EN)
• Top 10 Jobs for 2026 + Skills Path (ES / EN)
• 12-Week Plan — AI Consulting Foundation
• Prompt Engineering
• Dental Careers in Miami-Dade and South Florida
• AI-Generated HR Dashboard

Problems That Cannot Wait:

Home Problems That Cannot Wait

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Document Problems That Cannot Wait

Car Problems That Cannot Wait

Small Business Problems That Cannot Wait

Job Search Problems That Cannot Wait

Senior Tech Problems That Cannot Wait

Digital Scam Problems That Cannot Wait

Rental / Tenant Problems That Cannot Wait

Health Appointment Problems That Cannot Wait

Money Problems That Cannot Wait

English Series:

• English Fluency Teacher Serie 1
• English Fluency Teacher Serie 2
• English Fluency Teacher Serie 3

Ecosistema Moderno de Datos:

Basic:

• From Raw Data to Intelligent Decisions: A Series to Understand the Modern Data Ecosystem
• PowerShell for Clean Data: 20 Practical Use Cases That Build Trust
  • PowerShell_Topic_1_Bulk File Name Cleaning
  • PowerShell_Topic_2_Extract Numbers From File Names
  • PowerShell_Topic_3_Rename_Files_Using_Official_List
  • PowerShell_Topic_4_Move_Found_And_Not_Found_Files
  • PowerShell_Topic_5_Detect_Duplicates_By_Name
  • PowerShell_Topic_6_Detect_Duplicates_By_Hash
  • PowerShell_Topic_7_Create_Processed_Files_Reports
  • PowerShell_Topic_8_Validate_Files_Against_Active_Employees
  • PowerShell_Topic_9_Normalize_File_Extensions
  • PowerShell_Topic_10_Remove_Temporary_Or_Junk_Files
  • PowerShell_Topic_11_Standardize_CSV_Columns
  • PowerShell_Topic_12_Trim_Spaces_Before_And_After_Values
  • PowerShell_Topic_13_Find_Blank_Or_Incomplete_Values
  • PowerShell_Topic_14_Validate_Email_Formats
  • PowerShell_Topic_15_Compare_Two_CSV_Files_And_Find_Differences
  • PowerShell_Topic_16_Split_A_Large_File_Into_Smaller_Files
  • PowerShell_Topic_17_Merge_Multiple_CSV_Files_Into_One
  • PowerShell_Topic_18_Create_Error_Logs_During_Processing
  • PowerShell_Topic_19_Run_Scheduled_Cleanup
  • PowerShell_Topic_20_Generate_Final_Package_Ready_For_BI_Or_System_Upload
• Python as an Engine for Data Cleaning, Matching, and Auditing
  • Python_Topic_1_Normalize_Inconsistent_Columns
  • Python_Topic_2_Detect_Critical_Missing_Values
  • Python_Topic_3_Validate_Corporate_Emails
  • Python_Topic_4_Clean_Dates_With_Mixed_Formats
  • Python_Topic_5_Read_Data_From_SQL_Server
  • Python_Topic_6_Match_Excel_Against_SQL
  • Python_Topic_7_Read_Tables_From_Microsoft_Access
  • Python_Topic_8_Detect_True_Duplicates_Using_Rules
  • Python_Topic_9_Split_Full_Names_Into_Parts
  • Python_Topic_10_Create_Exception_Flags
  • Python_Topic_11_Clean_Open_Ended_Survey_Responses
  • Python_Topic_12_Classify_Comments_With_Simple_Rules
  • Python_Topic_13_Create_Summary_Tables_For_Dashboards
  • Python_Topic_14_Detect_Out_Of_Range_Expenses
  • Python_Topic_15_Validate_Allowed_Combinations
  • Python_Topic_16_Enrich_A_Table_Using_An_API
  • Python_Topic_17_Standardize_Departments_Or_Categories
  • Python_Topic_18_Compare_Two_Versions_Of_A_Table
  • Python_Topic_19_Export_Results_Into_Multiple_Tabs
  • Python_Topic_20_Create_A_Repeatable_Cleaning_Pipeline
• R as a Statistical Lab for Clean Data, Models, and Decisions
  

  R_Topic_1_Inspect_The_Real_Structure_Of_A_Table

  R_Topic_2_Clean_Text_Columns_With_Spaces_And_Casing_Issues

  R_Topic_3_Measure_Missing_Data_Percentage_By_Column

  R_Topic_4_Identify_Duplicates_By_Field_Combination

  R_Topic_5_Create_Year_Month_And_Quarter_Variables

  R_Topic_6_Create_Statistical_Summaries_By_Group

  R_Topic_7_Plot_The_Distribution_Of_A_Variable

  R_Topic_8_Detect_Outliers_Using_IQR

  R_Topic_9_Join_Two_Tables_By_A_Common_Key

  R_Topic_10_Find_Records_That_Do_Not_Match

  R_Topic_11_Create_A_Pivot_Style_Table

  R_Topic_12_Convert_Likert_Responses_Into_Numbers

  R_Topic_13_Count_Frequent_Words_In_Comments

  R_Topic_14_Measure_Relationship_Between_Two_Variables

  R_Topic_15_Compare_Averages_Between_Two_Groups

  R_Topic_16_Create_A_Basic_Linear_Regression

  R_Topic_17_Create_Behavior_Groups_Using_Clustering

  R_Topic_18_Analyze_Monthly_Trend

  R_Topic_19_Export_Results_To_Excel_With_Multiple_Sheets

  R_Topic_20_Create_A_Reproducible_R_Markdown_Report

• SQL Queries as the Foundation for Data Cleaning, Control, and Trust
  

  SQL_Topic_1_Review_The_First_Records_In_A_Table

  SQL_Topic_2_Find_Empty_Critical_Fields

  SQL_Topic_3_Normalize_Spaces_In_Text_Columns

  SQL_Topic_4_Detect_Duplicate_IDs

  SQL_Topic_5_Detect_Possible_Duplicates_By_Name_And_Date

  SQL_Topic_6_Find_Active_Employees_Without_Department

  SQL_Topic_7_Join_Employees_With_Departments

  SQL_Topic_8_Find_Records_Without_A_Match_In_The_Master_Table

  SQL_Topic_9_Count_Records_By_Department

  SQL_Topic_10_Group_Transactions_By_Month

  SQL_Topic_11_Create_A_Ranking_By_Total_Amount

  SQL_Topic_12_Compare_Each_Record_Against_Its_Group_Average

  SQL_Topic_13_Get_The_Latest_Record_By_Employee

  SQL_Topic_14_Validate_Allowed_Codes

  SQL_Topic_15_Create_Categories_With_Business_Logic

  SQL_Topic_16_Detect_Transactions_Outside_Business_Hours

  SQL_Topic_17_Compare_Current_Month_Against_Previous_Month

  SQL_Topic_18_Create_A_Clean_View_For_Power_BI

  SQL_Topic_19_Insert_Clean_Data_Into_A_Staging_Table

  SQL_Topic_20_Create_A_Data_Quality_Report

• Excel as a Hub for Data Cleaning, Validation, and Decision-Making
  

  Excel_Topic_1_Convert_Ranges_Into_Structured_Tables

  Excel_Topic_2_Create_Dropdown_Lists_To_Control_Inputs

  Excel_Topic_3_Retrieve_Official_Values_From_A_Master_Table

  Excel_Topic_4_Control_Errors_Without_Hiding_Problems

  Excel_Topic_5_Detect_Repeated_IDs_With_COUNTIF

  Excel_Topic_6_Clean_Invisible_Spaces_In_Text

  Excel_Topic_7_Standardize_Uppercase_And_Lowercase_Text

  Excel_Topic_8_Validate_Out_Of_Range_Dates

  Excel_Topic_9_Simplify_Complex_Formulas_With_LET

  Excel_Topic_10_Create_Dynamic_Exception_View

  Excel_Topic_11_Extract_Unique_Values_For_A_Catalog

  Excel_Topic_12_Summarize_Amounts_By_Multiple_Criteria

  Excel_Topic_13_Count_Records_Using_Combined_Rules

  Excel_Topic_15_Split_Columns_By_Delimiter

  Excel_Topic_16_Unpivot_To_Convert_Columns_Into_Rows

  Excel_Topic_17_Create_An_Executive_Summary_With_Pivot_Table

  Excel_Topic_18_Highlight_Exceptions_Visually

  Excel_Topic_19_Create_A_Data_Quality_Status_Column

  Excel_Topic_20_Create_A_Mini_Control_Dashboard

• Power BI Desktop as the Bridge Between Data, Models, and Executive Decisions
  

  PowerBI_Topic_1_Connect_To_Multiple_Data_Sources

  PowerBI_Topic_2_Clean_Data_Before_Loading_Into_The_Model

  PowerBI_Topic_3_Create_A_Star_Schema_Model

  PowerBI_Topic_4_Create_Relationships_Between_Tables

  PowerBI_Topic_5_Create_A_Base_Count_Measure

  PowerBI_Topic_6_Create_A_Total_Amount_Measure

  PowerBI_Topic_7_Calculate_Percentage_Of_Records_With_Issues

  PowerBI_Topic_8_Create_A_Calendar_Table

  PowerBI_Topic_9_Compare_Current_Month_Against_Previous_Month

  PowerBI_Topic_10_Create_Executive_Cards

  PowerBI_Topic_11_Use_Slicers_For_Navigation

  PowerBI_Topic_12_Create_Hierarchies_For_Drill_Down

  PowerBI_Topic_13_Design_Custom_Tooltips

  PowerBI_Topic_14_Create_A_Data_Quality_Page

  PowerBI_Topic_15_Create_A_Traffic_Light_Measure

  PowerBI_Topic_16_Apply_Colors_Based_On_Rules

  PowerBI_Topic_17_Prepare_Row_Level_Security

  PowerBI_Topic_18_Create_Navigation_With_Bookmarks

  PowerBI_Topic_19_Optimize_The_Model_For_Speed

  PowerBI_Topic_20_Publish_And_Prepare_Scheduled_Refresh

Advanced:

• PowerShell for Data Cleaning: 20 Advanced Cases
  

  powershell_advanced_topic_01_capitalize_names_revised_footer

  powershell_advanced_topic_02_standardize_phone_numbers

  powershell_advanced_topic_03_remove_accents_special_characters

  powershell_advanced_topic_04_standardize_state_city_names

  powershell_advanced_topic_05_normalize_date_formats

  powershell_advanced_topic_06_validate_zip_code_length

  powershell_advanced_topic_07_identify_illogical_dates

  powershell_advanced_topic_08_validate_email_domains

  powershell_advanced_topic_09_detect_numeric_outliers

  powershell_advanced_topic_10_check_url_existence

  powershell_advanced_topic_11_fill_null_or_empty_fields

  powershell_advanced_topic_12_extract_email_domain

  powershell_advanced_topic_13_split_full_name_columns

  powershell_advanced_topic_14_generate_row_checksum

  powershell_advanced_topic_15_audit_metadata

  powershell_advanced_topic_16_data_profiling_report

  powershell_advanced_topic_17_orphan_records

  powershell_advanced_topic_18_clean_invisible_line_breaks

  powershell_advanced_topic_19_mask_sensitive_data_pii

  powershell_advanced_topic_20_compress_clean_data_for_transmission

• Python Pro: 20 Cases for Data Engineering and AI
  

  python_advanced_topic_01_fuzzy_matching

  python_advanced_topic_02_anomaly_detection_isolation_forest

  python_advanced_topic_03_smart_null_imputation

  python_advanced_topic_04_semantic_search_embeddings

  python_advanced_topic_05_feedback_sentiment_analysis

  python_advanced_topic_06_process_massive_files_polars

  python_advanced_topic_07_asynchronous_api_requests

  python_advanced_topic_08_real_parallelism_in_transformations

  python_advanced_topic_09_direct_data_lake_reading_s3

  python_advanced_topic_10_flattening_nested_json

  python_advanced_topic_11_extract_data_with_login_and_js

  python_advanced_topic_12_extracting_scanned_tables

  python_advanced_topic_13_regex_with_named_capture_groups

  python_advanced_topic_14_connection_graph_analysis

  python_advanced_topic_15_strict_pre_production_validations

  python_advanced_topic_16_interactive_html_reports

  python_advanced_topic_17_sensitive_data_masking

  python_advanced_topic_18_unit_tests_for_data_cleaning

  python_advanced_topic_19_gps_coordinate_calculations

  python_advanced_topic_20_resampling_and_interpolation

• The R Laboratory: Analytics, Models, and Automation
• SQL Auditing: 20 Queries to Detect Risk
• Excel as a Forensic Data Quality Lab
• Power BI as a Data Quality Command Center

Financial Ratios BI Course:

Financial Ratios BI Course Overview

Topic 1 – Create Synthetic Financial Companies Dataset

Topic 2 – Create the Chart of Accounts

Topic 3 – Generate Synthetic Trial Balance

Topic 4 – Validate the Trial Balance

Topic 5 – Map Accounts to Financial Statements

Topic 6 – Build the Income Statement

Topic 7 – Build the Balance Sheet

Topic 8 – Build Cash Flow Indicators

Topic 9 – Create Market Data

Topic 10 – Liquidity Ratios

Topic 11 – Profitability Ratios

Topic 12 – Debt Ratios

Topic 13 – Operating Performance Ratios

Topic 14 – Cash Flow Indicator Ratios

Topic 15 – Investment Valuation Ratios

Topic 16 – Data Quality Issues

Topic 17 – SQL Server Financial Model

Topic 18 – Power BI Model Preparation

Topic 19 – Executive Financial Dashboard Dataset

Topic 20 – Final Training Package

Topic 21 – Deploy Financial Ratios BI Model to SQL Server

Topic 22 – Power BI DAX Ratio Measures

Topic 23 – Compare Precalculated Ratios vs DAX Ratios

Topic 24 – Build Dynamic Financial Ratio Cards

Topic 25 – Build Company and Period Ratio Trends

Topic 26 – Executive Dashboard Using DAX Measures

Power Query vs SQL:

power_query_vs_sql_series_01 Core Transformation Map.html

power_query_vs_sql_series_02 Merge Is Not Append.html

power_query_vs_sql_series_03 Merge Queries vs SQL JOIN.html

power_query_vs_sql_series_04_append_union_all.html

power_query_vs_sql_series_05_remove_duplicates_group_by.html

power_query_vs_sql_series_06_conditional_case_when.html

power_query_vs_sql_series_07_replace_values_case_replace.html

power_query_vs_sql_series_08_change_type_cast_convert.html

power_query_vs_sql_series_09_split_column_text_parsing.html

power_query_vs_sql_series_10_pivot_unpivot.html

power_query_vs_sql_series_11_fill_down_window_logic.html

power_query_vs_sql_series_12_applied_steps_sql_script.html

Dax Function:

• CALCULATE with Filter Sets {} in DAX
• CALCULATE con Sets de Filtros `{}` en DAX
• Top 15 DAX Functions You Must Know
• DAX Analysis — IF vs SWITCH (Extended)
• From folders to data
• Power BI Quick Practice: 10 LinkedIn Posts
• BI for Humans AI Skills Library
• Advanced data quality checks season_2
• From a Raw Open Data CSV to a Power BI-Ready Data Warehouse

POST LinkedIn:

sql_data_quality_checks_10_linkedin_posts.html

data_security_checks_10_linkedin_posts.html

data_governance_checks_10_linkedin_posts.html

data_privacy_checks_10_linkedin_posts.html

data_ethics_checks_10_linkedin_posts.html

data_literacy_checks_10_linkedin_posts.html

data_reliability_checks_10_linkedin_posts.html

data_modeling_checks_10_linkedin_posts.html

ai_data_readiness_checks_10_linkedin_posts.html

dashboard_trust_checks_10_linkedin_posts.html

Pandas Use Cases:

Pandas_Use_Case_01_Load_Inspect_Messy_City_Service_Data.html

Pandas_Use_Case_02_Standardize_Text_and_Category_Values.html

Pandas_Use_Case_03_Clean_and_Convert_Mixed_Date_Formats.html

Pandas_Use_Case_04_Handle_Missing_Values_Strategically.html

Pandas_Use_Case_05_Detect_and_Remove_Exact_Duplicates.html

Pandas_Use_Case_06_Resolve_Conflicting_Duplicate_Request_IDs.html

Pandas_Use_Case_07_Validate_Numeric_Ranges_and_Business_Rules.html

Pandas_Use_Case_08_Validate_ZIP_Codes,_Phones,_and_Emails.html

Pandas_Use_Case_09_Validate_Latitude_and_Longitude.html

Pandas_Use_Case_10_Create_Data_Quality_Flags.html

Pandas_Use_Case_11_Build_a_Data_Quality_Score_per_Record.html

Pandas_Use_Case_12_Create_a_Clean_Master_Dataset.html

Pandas_Use_Case_13_Analyze_Requests_by_Service_Type.html

Pandas_Use_Case_14_Analyze_Requests_by_Department.html

Pandas_Use_Case_15_Analyze_Requests_by_City_and_ZIP_Code.html

Pandas_Use_Case_16_Measure_Resolution_Time_and_SLA_Performance.html

Pandas_Use_Case_17_Analyze_Request_Channels.html

Pandas_Use_Case_18_Analyze_Satisfaction_Scores.html

Pandas_Use_Case_19_Detect_Trends_and_Operational_Patterns.html

Pandas_Use_Case_20_Build_an_Executive_City_Service_Summary.html

ChatGPT City Government Use Case:

ChatGPT_City_Government_Use_Case_01_Project_Initiation_for_a_Municipal_Service_Portal.html

ChatGPT_City_Government_Use_Case_02_Requirements_Gathering_for_Resident_and_Department_Needs.html

ChatGPT_City_Government_Use_Case_03_Scope_Definition_and_Municipal_Work_Breakdown_Structure.html

ChatGPT_City_Government_Use_Case_04_Schedule_Planning_and_Municipal_Milestones.html

ChatGPT_City_Government_Use_Case_05_Resource_Planning_and_Municipal_RACI.html

ChatGPT_City_Government_Use_Case_06_Cost_Estimation_and_Municipal_Budget_Support.html

ChatGPT_City_Government_Use_Case_07_Risk_Management_for_a_City_Technology_Project.html

ChatGPT_City_Government_Use_Case_08_Quality_Planning,_Testing,_and_Municipal_Acceptance.html

ChatGPT_City_Government_Use_Case_09_Communication_Management_and_Public-Sector_Reporting.html

ChatGPT_City_Government_Use_Case_10_Procurement_and_Vendor_Evaluation_for_Municipal_Technology.html

ChatGPT_City_Government_Use_Case_11_Monitoring,_Control,_and_Municipal_Change_Management.html

ChatGPT_City_Government_Use_Case_12_Municipal_Project_Closure_and_Lessons_Learned.html

Learning by Doing:

• Python Topic #1 — Learning by Doing Introduction
• Python Topic #2 — Learning by Doing : Clean Data in Minutes with Python
• Python Topic #3 — Learning by Doing : Python + SQL Server + California Crashes
• Python Topic #4 — Learning by Doing : CCRS California Crashes Executive Analytical Report
• Python Topic #5 — Learning by Doing : CCRS California Crashes Business Intelligence Risk Discovery Report
• Python Topic #6 — Learning by Doing : CCRS California Crashes — Machine Learning Validation & Post-Model BI Investigation
• Business Intelligence # 1 — Learning by Doing : NYC Building Permits — Permit Processing & Urban Development Intelligence
• Business Intelligence # 2 — Learning by Doing : City of Miami 311 Service Requests
• Business Intelligence # 3 — Learning by Doing : From Open Data to Executive Intelligence Fire Inspections
• Successful Practices for High-Impact Technical Posts
• Business_Investigation_1_Airline_Operational_Performance
• Business_Investigation_2_Police_Incident_Operational_Intelligence
• Business_Recognition_Process

Electronic Business Card Project:

• Business Card Directory Project
• Business Model
• Hialeah-Hialeahoficios.com Web Page
• Miami-Miamioficios.com Web Page
• Electrical Blue Print and Specifications (Demo Class)
• Structure and Function of the Body_I (Demo Class)
• Nursing Skills and Techniques (Demo Class)
• Principles of Radiography (Demo Class)
• Principles of Electrocardiography (Demo)
• Special Occupational Code NEC3 (Demo Class)
• Commercial Refrigeration I (Demo Class)
• PLB_501_Gas_and_Troubleshooting (Demo Class)
• Electrical Systems (Demo Class)
• Residential Wiring I (Demo Class)
• Distance Hybrid Education Administration Training Proposal
• Institutional Administrative Training
• SF_Institute_Unified_Academic_and_Workforce_Alignment_System_Accreditation_Prop
• Faculty Academic Materials Management Program
• Online Faculty Continuing Education Program Proposal
• Faculty Academic Materials Management Online Training
• Human_AI_Decision_Intelligence_Framework_Road_Safety
• Hypothesis_Explorer
• Accela Local Analytical Continuity & BI Platform