Curs de Data Analyst & Data Engineer

• Inside the Analyst’s World: role, tools, and mindset
• Excel jumpstart: Data analysis foundations

• Excel meets statistics: Crunching numbers for insights
• Excel Analytics mastery: From statistics to insights

• Digging into databases: SQL fundamentals
• SQL unleashed: Advanced querying techniques

• Loading, cleaning & exploring data
• Power BI: From data to dashboard

Storytelling through reports & dashboards:

• Visual storytelling in Power BI: charts and graphs
• Power BI Report Builder: Crafting interactive dashboards

• Bringing it all together: End-to-End project build
• Project Showcase: Final presentations and wrap-Up

KPIs, metrics & Grafana dashboards:

• From metrics to monitoring: KPIs and Grafana Introduction
• Grafana Dashboards: Real-time insights for analysts

– Numbers and calculations
– Variables and formulas
– Boolean logic and conditionals
– Sets and collections
– Functions as recipes
– Patterns, repetition, loops, recursion
– Numeral systems, binary thinking
– Programming intro
– Problem solving
– Control Flow Graph diagrams

– Program structure
– Development environment setup
– Basic I/O
– Variables, data types and operators
– Strings
– Control flow statements – conditionals

– Data structures
– Control flow statements – loops
– Finding min and max
– Sorting algorithms
– Search algorithms

– Lists
– Tuples
– Sets
– Dictionaries

– Comprehensions
– Special collections

– Fundamentals
– Recursion
– Lambda functions
– Callbacks

– Modules, packages, libraries
– Building your own module and package
– PIP and third-party libraries
– Error handling
– Files
– JSON
– CSV

– Logging
– File paths
– Shutil
– Pattern building blocks
– Core re functions

– Classes and objects
– Constructors
– Attributes and methods
– String representations
– Data classes
– OOP Principles in practice

– Abstract base classes
– Custom exceptions
– TypedDict
– Enums
– Applied SOLID patterns
– Recap session

– Statistics intro
– NumPy – the array foundation
– Pandas Series and DataFrame
– Loading and inspecting data
– Descriptive statistics
– Selecting and filtering rows and columns
– Cleaning data
– Reshaping data
– Inferential statistics and scipy

– Matplotlib
– Plotly
– Seaborn

– Web intro
– Requests
– Flask and REST APIs
– Dash

– minimum AI for data engineers
– using LLMs for coding, other tasks
– online/offline
– update LLM context with you own documents

– concurency specific problems

– using multiple threads
– using multiple processes

– general automations
– Computer Vision
– building jobs / pipelines

– web scraping / collect data

– Database interaction and connectors
– SQL
– MongoDB

– docker / containers
– virtual machines
– cloud services and instances