kingers Posted March 18 Report Share Posted March 18 Master Sql For Data Analysis: From Beginner To Advanced Published 3/2025 MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz Language: English | Size: 1.31 GB | Duration: 6h 3mLearn SQL from scratch for data analysis, BI, and data science. Write queries, optimize, and work with cloud databases! What you'll learn Master SQL for Data Analysis - Follow a structured, hands-on approach to transform raw data into meaningful insights. Solve Real-World Data Challenges - Work on practical, project-based problems that mimic real business scenarios. Write Powerful SQL Queries for Data Manipulation - Learn to extract, filter, aggregate, and transform complex datasets efficiently. Unlock the Power of Joins & Multi-Table Analysis - Master INNER, LEFT, RIGHT, FULL, SELF, and CROSS JOINs to combine data like a pro. Analyze Trends with Window Functions - Use RANK, LAG, LEAD, NTILE, and more to perform advanced data analysis. Optimize Performance for Big Data - Learn best practices for indexing, query tuning, and handling millions of records with ease. Master Subqueries & Common Table Expressions (CTEs) - Break down complex problems into manageable, efficient queries. Requirements This course is suitable for all learners and no knowledge required and who want to strengthen their skills and prepare for Data Analysis. Description Master SQL for Data Analysis: From Beginner to AdvancedThis course has been completely designed from the ground up to give you a comprehensive, hands-on learning experience in SQL for data analysis. Whether you're a beginner with no prior experience or someone looking to enhance your SQL and data analytics skills, this course will take you through everything from fundamental queries to advanced SQL techniques used by data analysts, data scientists, and business intelligence professionals.If you've ever wanted to extract meaningful insights from data, but felt overwhelmed by databases, this course is for you! We take a practical, step-by-step approach, ensuring that you don't just learn SQL-you master it.Why Learn SQL for Data Analysis?SQL is one of the most in-demand skills for data analysts, data scientists, and business intelligence professionals. Companies like Google, Netflix, Amazon, Airbnb, and Facebook use SQL to extract insights, analyze trends, and make data-driven decisions.This course focuses not just on writing queries, but also on real-world applications, including data visualization, performance tuning, and cloud-based SQL environments like Snowflake, BigQuery, and PostgreSQL.What You'll Learn:SQL Basics: Build a Strong FoundationUnderstand relational databases and how SQL works.Learn to write queries, retrieve data, and filter results.Use WHERE, ORDER BY, and LIMIT to refine your queries.Data Analysis with SQL: Aggregations & ReportingGroup and summarize data with GROUP BY and HAVING.Use aggregate functions like SUM, AVG, COUNT, MIN, and MAX to analyze datasets.Perform advanced filtering and sorting to extract meaningful insights.Mastering SQL Joins & SubqueriesLearn INNER, LEFT, RIGHT, and FULL OUTER JOINS to combine data from multiple tables.Work with subqueries and Common Table Expressions (CTEs) to break down complex queries.Advanced SQL Techniques: Analytics & Performance OptimizationMaster Window Functions like RANK, LEAD, LAG, NTILE, and DENSE_RANK for time-series and ranking analysis.Use CASE statements, COALESCE, and NULL handling for data transformation.Optimize queries with indexes, query execution plans, and performance tuning.Python + SQL: The Best of Both WorldsLearn how to connect SQL with Python's Pandas library for data manipulation.Extract, clean, and visualize SQL data using Python and Pandas.Build automated reporting pipelines with Python and SQL.Real-World Projects & Hands-On LearningThis course is packed with hands-on exercises, coding challenges, and real-world projects that will reinforce your learning. You will apply your SQL skills to:By the end of this course, you'll have a portfolio of SQL projects to showcase your expertise!Who is This Course For? spiring Data Analysts & Data Scientists looking for hands-on SQL experience. Business & Marketing Professionals who want to analyze and visualize company data. Python Users who want to integrate SQL with Pandas for data analysis. Developers & Engineers who want to write better, optimized SQL queries. Anyone who wants to master SQL for real-world data analysis!What Makes This Course Different? Engaging & Hands-On - This isn't just another theory-based course! You'll write SQL queries within minutes and work on real-world projects. Project-Based Learning - Apply what you learn immediately with practical exercises and data analysis case studies. Clear & Structured Approach - No fluff, just step-by-step guidance from SQL basics to advanced analytics. SQL + Python Integration - Future-proof your learning by connecting SQL with Python's Pandas for advanced data analysis. Real-World Applications - Master SQL for business intelligence, data science, and analytics roles.By the End of This Course, You Will: Write and optimize SQL queries like a pro. Analyze data efficiently using SQL's powerful functions. Integrate SQL with Python Pandas for in-depth analysis. Work with real-world datasets and gain hands-on experience. Build a strong SQL portfolio with multiple projects.This isn't just another course where you watch me code for hours-it's an interactive learning experience that will empower you to work confidently with SQL and data analysis.So, let's get started! Enroll today and start mastering SQL for Data Analysis! Overview Section 1: Introduction Lecture 1 Introduction Section 2: Database Quickstart Lecture 2 Installation: Mac Lecture 3 Installation: Windows Section 3: Database & Schema Lecture 4 Database Operations Section 4: Tables Lecture 5 Create Base Tables Lecture 6 Insert into Tables Lecture 7 Create and Drop Tables Section 5: Basics Lecture 8 Select Columns Lecture 9 Experiments: Select Lecture 10 Experiments: Select 2 Lecture 11 Experiments: Select (Without Tables) Lecture 12 Experiments: Mathematical Expression Lecture 13 Distinct Lecture 14 Experiments: Distinct Lecture 15 Key Takeaways: Distinct Lecture 16 Aggregate Functions Lecture 17 Key Takeaways: Aggregate Functions Lecture 18 Customer and Orders: Select Section 6: String Functions Lecture 19 String Functions Lecture 20 Sub-Strings Lecture 21 Concat Lecture 22 Key Takeaways: String Functions Lecture 23 Length Section 7: Limiting Records Lecture 24 Limit & Offset Lecture 25 Key Takeaways: Limit & Offset Section 8: Alias Lecture 26 Alias Lecture 27 Key Takeaways: Alias Section 9: Filters Lecture 28 Filters with Numeric Lecture 29 Key Takeaways: Numeric Lecture 30 Filters with String Lecture 31 Key Takeaways: String Lecture 32 Filters with Date Lecture 33 Key Takeaways: Date Lecture 34 Filters with Boolean Lecture 35 Key Takeaways: Boolean Lecture 36 IN Clause Lecture 37 Experiments: IN Lecture 38 Key Takeaways: IN Lecture 39 Between Lecture 40 Key Takeaways: Between Lecture 41 Like Lecture 42 Experiments: Like Lecture 43 Key Takeaways: Like Section 10: Changing Data Types Lecture 44 Cast: Decimal & Integers Lecture 45 Key Takeaways: Cast Section 11: Handling Data Lecture 46 Default Values Lecture 47 Handling Null Section 12: Data Analysis Lecture 48 Case: Conditional Functions Lecture 49 Coalesce Lecture 50 Null IF Section 13: Keys & Constraints Lecture 51 Keys: Primary, Foreign & Composite Key Lecture 52 Constraints: Unique Lecture 53 Constraints: Check Section 14: Sub-Queries Lecture 54 Inner Queries Lecture 55 Experiments: Inner Queries Section 15: Union & Intersect Lecture 56 Union Lecture 57 Experiments: Union Lecture 58 Union All Lecture 59 Experiments: Union All Lecture 60 Intersect Section 16: Group By Lecture 61 Group By Lecture 62 Group By with Having Lecture 63 Group By with Filters Lecture 64 Experiments: Group By Section 17: Sorting: Order By Lecture 65 Order By Lecture 66 Order By with Filters Section 18: Joins Lecture 67 Introduction: Inner Join Lecture 68 Example: Inner Join Lecture 69 Introduction: Left Join Lecture 70 Example: Left Join Lecture 71 Example: Right Join Section 19: Views Lecture 72 Views Lecture 73 Experiments: Views Lecture 74 Materialized: Views Section 20: Data Manipulation Language Lecture 75 Insert Rows Lecture 76 Update Rows Lecture 77 Delete Rows Lecture 78 Alter Tables Section 21: Temporary Tables Lecture 79 Temp Tables Section 22: Functions - UDFs Lecture 80 User Defined Functions Section 23: SQL with Python Lecture 81 Mac: Python Installation Lecture 82 Python - SQL Connectivity Aspiring Data Analysts & Business Analysts,Data Scientists & Machine Learning Enthusiasts,Marketing & Sales Professionals,Finance & Operations Analysts,Software Developers & EngineersTurboBithttps://turbobit.net/q35038e1ot35/Master.SQL.for.Data.Analysis.From.Beginner.to.Advanced.part1.rar.htmlhttps://turbobit.net/ksc2dkwz640y/Master.SQL.for.Data.Analysis.From.Beginner.to.Advanced.part2.rar.htmlRapidGatorhttps://rapidgator.net/file/09901d4e62fe02b9443e21cfca6a5c99/Master.SQL.for.Data.Analysis.From.Beginner.to.Advanced.part1.rarhttps://rapidgator.net/file/e51610f7ce38a6def70ab4752f5a83f2/Master.SQL.for.Data.Analysis.From.Beginner.to.Advanced.part2.rarFileFactory Link to comment Share on other sites More sharing options...
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