Computer Scientist committed to generating value and insights through data.
With more than 4 years of professional experience, including two years in the 4.0 industry and others in the retail and e-commerce sectors, I focus on problem-solving. Currently, I am part of the Pricing team at Americanas, the largest retailer in Brazil.
AI TOOLS AND FRAMEWORKS
Four years of experience with Python and building AI and Machine Learning models with Scikit Learn, Tensorflow, Pytorch and others.
GOOGLE CLOUD COMPUTING
Two years using GCP services such as BigQuery, Cloud Functions, Vertex AI, and Google Machine Learning to execute company projects.
AMAZON WEB SERVICES
One year of experience deploying machine learning models using AWS services.
DATA ENGINEERING TOOLS
Two years of experience with data engineering tools for data ingestion, organization, and management of data flow using Airflow, Docker, Kubernetes and Spark.
BUSINESS ANALYTICS
Experience with analysis and visualization tools to communicate and present results to both technical and non-technical teams.
OTHER LANGUAGES
Extensive knowledge in other programming languages for various purposes, with a focus on performance, such as C, C++, Rust, and Java.
Portfolio
- All
- Data Science
- AI
- ML Ops
- Others
SENTIMENT STOCKS AI
Python, DeepSeek, GPT, Ollama and Langchain
FRAUD DETECTION WITH LLM
Python, Ollama and Langchain
FINANCIAL SENTIMENT ANALYSIS USING FINBERT
Python, FastAPI, LLM and Docker
RAG TO CREATE EXTERNAL MEMORY FOR LLM
Python, RAG, Streamlit, LangChain and Docker
RAG TO CREATE EXTERNAL MEMORY FOR LLM
Python, Pytorch and RAG
WEBAPP FOR CHATBOT WITH OPENAI API
Python, Streamlit, Langchain and GPT Api
CHATBOT WITH LANGCHAIN AND GPT API
Python, Langchain and GPT Api
AI MEDICAL ASSISTENT
Python, Pytorch, Langchain and LLMs
AI ASSISTENT FOR HOSTING
Python, Pytorch and LLMs
AI LEGAL ASSISTENT
Python, LLMs and Docker
SENTIMENT ANALYSIS CLASSIFIER
Pytorch, LLMs, Docker and AWS
BIG MART SALES PREDICTION
Python and Tensorflow
BANK MARKETING CLASSIFIER
Apache Spark and MLlib
MARKETING ANALYTICS
Python and Scikit-Learn
HEALTH ANALYTICS
Python, AWS and SageMaker
RH ANALYTICS
PyData Stack and Flask
BANK MARKETING CLASSIFIER
Apache Spark and MLlib
MARIJUANA LEGALAIZE ANALYSIS
PyData Stack and Time Series
STOCK FORECASTING
PyData Stack, Streamlit and Time Series
FRAUD DETECTION
PyData Stack and Machine Learning
LOAN PREDICTOR CLASSIFIER
PyData Stack, Django and React js
POWER BI DASHBOARDS
Microsoft Power BI
SENTIMENTAL ANALYSIS
Python and NLP
PRICES FORECASTING
Python and Time Series
SPAM/HAM CLASSIFIER
Python and NLP
BRAZILIAN FOOTBALL CHAMPIONSHIP CLASSIFIER
Python and Scikit Learning
TENSORFLOW IMAGE CLASSIFIER
Python and Tensorflow
MUSIC GENERATION WITH DEEP LEARNING
Python and Deep Learning
HOUSE PRICES PREDICTOR
Python for Regression
PREDICTING TITANIC DISASTERS SURVIVORS
Python and Scikit-Learn
MY OWN PROGRAMMING LANGUAGE
Criação de Linguagem de programação
Blog
summary
For two years, I was a member of a company specializing in Industry 4.0 services for packaging companies. During this time, I worked as a Full Stack developer and was also responsible for managing data from industrial machines. I actively participated in a team that developed an intelligent system capable of collecting data from machines, to use artificial intelligence to create and to optimize both the production and dispatch queues, and additionally, the system included all the functionalities of an APS system.
Currently, I am a Data Scientist and Engineer at Americanas, working on data management, development, and deployment of Machine Learning and Artificial Intelligence models for the Pricing team. Our focus is on setting prices for products in physical stores, aiming to optimize sales and maximize profits.
As an individual, I always strive to give my best in whatever I do. I believe that offering solutions before complaining or criticizing is an important step in changing the world around you and making a difference.
I am passionate about two-wheeled adventures, a fan of Chopin and playing his compositions on the piano, a bodybuilder, and a hobbyist cook in my spare time.
🎹 💪 🏍 👨🍳Education
BACHELOR OF COMPUTER SCIENCE
2017 - 2021
University of West Paulista, Presidente Prudente, SP
During college, I participated in programming marathons, hackathons, and various events in the field of computer science.
My graduation project focused on Computer Vision, where I applied the use of Artificial Intelligence to identify and monitor individuals through video and detect movements that could indicate a potential criminal act.
You can read my scientific article here: Use of Deep Learning applied in the recognition of human actions from high resolution videos in order to identify suspicious movements
- Participation in several SBC programming marathons;
- Participation in events promoted by the faculty such as Lectures, Short Courses, Hackathons, etc.;
- Collaboration in several voluntary actions during my academic life.
MACHINE LEARNING ENGINEERING TRAINING (360 HOURS)
2025 - 2025
Data Science Academy, Brazil
This program equipped me with both theoretical and hands-on experience in deploying Machine Learning models and managing their lifecycle using best practices in software engineering, DevOps, and MLOps.
Key Learnings:
- Software Engineering for Machine Learning: Designing robust architectures, building APIs, and deploying web applications integrated with ML models using Python and Rust;
- Model Deployment and Automation: Implementing versioning, retraining strategies, and building Feature Stores for scalable and reusable pipelines;
- MLOps and CI/CD: Automating model training, testing, and deployment workflows using tools like GitHub Actions, Kubernetes, AWS SageMaker, and Lambda Functions;
- LLMOps and Generative AI: Deploying and monitoring RAG pipelines and LLMs, and creating test automation flows for intelligent agents and AI modules.
You can see the certificate here: Certificate of Completion
AI ENGINEERING TRAINING (384 HOURS)
2024 - 2025
Data Science Academy, Brazil
This program provided me with both theoretical and practical knowledge of cutting-edge AI techniques in the fields of Natural Language Processing, Computer Vision and Financial Optimization.
Key Learnings:
- Deep Learning with Python and C++: Building models from scratch, implementing attention mechanisms, and fine-tuning transformer models for various applications;
- Computer Vision: Applying Vision Transformers, image segmentation, and integrating text-to-image generation techniques using Stable Diffusion;
- Generative AI and LLMs: Developing personalized assistants with LangChain, fine-tuning open-source LLMs, and creating intelligent agents for practical tasks;
- Financial Engineering with AI: Predicting asset prices, detecting fraud, and automating trading strategies using AI.
You can see the certificate here: Certificate of Completion
Professional Experience
Data Scientist & Engineer
2022 - current
Americanas SA.
I currently work as a Data Scientist and Engineer at Americanas S.A. Americanas S.A. is the result of the merger between Lojas Americanas and B2W. It owns the biggest brands on the Internet (Americanas.com, Submarino, Shoptime and SouBarato), with a marketplace, logistics and fintech operation linked to more than 1700 physical stores throughout Brazil.
I work on data management, development, and deployment of Machine Learning and Artificial Intelligence models for the Pricing team. Our focus is on setting prices for products in physical stores, aiming to optimize sales and maximize profits.
ETL Developer (Freelancer)
2022 - 2022
Unilotus Food Distributor Ltd.
I developed an ETL project to organize data received in a completely unstructured file. Previously, my client spent about 5 hours per day sorting through the unreadable file received from their supplier. With the developed application, this time has been reduced to less than 1 minute.
The application is a web system developed in Python and Flask that receives either a .txt or .xml file. After transformations, it returns to the user an Excel file with the data organized into columns chosen by the user.
Full Stack Developer
2019 - 2021
Play Intelligent Systems Ltd.
At Play Sistemas, I worked on all stages of the project (end-to-end), from the initial phase - requirements gathering, to the final deployment of the web system. I used the following technologies: HTML, CSS3, and JavaScript for Front-end development; C#, ASP.NET, Entity Framework for Back-end development; PL/SQL for database manipulation; Development of APIs for integration of the company's system with industrial machines using low-level programming; Microsoft Azure for version control and website deployment on cloud services.
I worked with optimization and genetic algorithms, database migration, and various other topics in advanced computing. However, the most valuable lesson I learned and carry forward was: "Be an expert in the company's business and a problem solver," and indeed, these are essential qualities for an IT professional.
Courses
CI/CD PIPELINES FOR MACHINE LEARNING AND AI OPERATIONS
April 2025
DSA - Data Science Academy
Course 4/4 of the Data Science Academy ML Engineer Training
The course covers Continuous Integration (CI) and Continuous Deployment (CD) practices applied to Machine Learning projects, with a focus on automation, versioning, and pipeline reproducibility. It presents workflows for the automated execution of training, testing, and deployment processes. The training includes eight hands-on projects, progressing from manual processes to advanced automations using tools like SageMaker, Kubernetes, and GitHub Actions—ranging from behavior prediction to testing agents and RAG modules for AI applications.
MLOPS AND MACHINE LEARNING MODEL LIFECYCLE
April 2025
DSA - Data Science Academy
Course 3/4 of the Data Science Academy ML Engineer Training
The course offers a hands-on immersion in the operationalization of Machine Learning projects through MLOps, covering everything from fundamentals such as version control, automation, Feature Store, and CI/CD, to advanced topics like AIOps, LLMOps, Generative AI, and RAG. Throughout the journey, students explore the complete lifecycle of ML models, from conception to deployment, with a focus on building sustainable and scalable solutions. The training includes the creation of inference pipelines, real-time prediction, model monitoring, and automated cloud deployment. The technologies and tools taught include MLflow, Optuna, Feature Store, infrastructure as code (IaC) with Terraform, as well as the integration of frontend, backend, and APIs to operationalize solutions with generative models and LLMs.
DEVELOPMENT AND DEPLOYMENT OF MACHINE LEARNING MODELS
March 2025
DSA - Data Science Academy
Course 2/4 of the Data Science Academy ML Engineer Training
Machine Learning has matured, and now the focus is on how to implement and maintain models in production. Companies need to tackle challenges such as deployment, resource reuse, monitoring, drift detection, and versioning of models. The course addresses these topics, using Python for prototypes and Rust for production performance. Students will participate in various hands-on projects, such as: building and deploying models for logistics, churn prediction with RandomForest, cloud deployment on AWS, text generation with LLM from images, building a Feature Store, retraining and versioning models, drift mitigation, and API deployment in Rust. These projects aim to provide comprehensive training to face current challenges in Machine Learning.
SOFTWARE ENGINEERING FOR MACHINE LEARNING
March 2025
DSA - Data Science Academy
Course 1/4 of the Data Science Academy ML Engineer Training
The course teaches the integration of software development with Machine Learning, providing a solid foundation in ML system design, requirements engineering, and software development practices. It includes two main projects: developing a web application with ML integration and deploying an API for Bitcoin price prediction.
FINANCIAL ENGINEERING WITH ARTIFICIAL INTELLIGENCE
January 2025
DSA - Data Science Academy
Course 4/4 of the Data Science Academy AI Engineer Training
The course explores the intersection between Finance and Artificial Intelligence, covering the fundamentals of Financial Engineering and advanced AI techniques applied to the sector. With a modular structure, it spans from basic topics to advanced subjects such as hedging, derivatives, and the use of LLMs. Students develop practical skills through 10 projects based on real-world scenarios, including asset price prediction, sentiment analysis in financial news, fraud detection, and the creation of investor robots. The focus is on equipping professionals to meet the growing demand for data analysis and AI in the financial market.
ARTIFICIAL INTELLIGENCE FOR COMPUTER VISION
December 2024
DSA - Data Science Academy
Course 2/4 of the Data Science Academy AI Engineer Training
The course delves into Computer Vision, starting from the fundamentals to advanced techniques, with a practical focus on tools like the HuggingFace library, pre-trained model customization, convolutional neural networks (CNNs), and transformers, including Vision Transformers (ViT) and their variations. It also covers state-of-the-art AI techniques, such as "Text-to-Image with Stable Diffusion".
GENERATIVE AI AND LLMS FOR NATURAL LANGUAGE PROCESSING
November 2024
DSA - Data Science Academy
Course 3/4 of the Data Science Academy AI Engineer Training
The course offers a comprehensive journey into the field of Artificial Intelligence (AI), focusing on Generative AI, Large Language Models (LLMs), and Natural Language Processing (NLP). It covers fundamental and advanced topics, such as Transformers, Few-Shot Learning, Transfer Learning, Fine-Tuning, PEFT, LoRa, RLHF, RAG, and Llama 2.
Through a practical approach, students will explore cutting-edge technologies like OpenAI GPT, LangChain, Open-Source LLMs, and AWS, applying this knowledge to real-world projects to address real-world challenges.
The course is modular, combining theory and practice, with well-structured chapters followed by practical projects that ensure an immersive experience. It aims to empower students to leverage AI's potential in an ever-evolving job market, emphasizing the importance of extracting insights and automating processes as a critical competitive advantage.
Through a practical approach, students will explore cutting-edge technologies like OpenAI GPT, LangChain, Open-Source LLMs, and AWS, applying this knowledge to real-world projects to address real-world challenges.
The course is modular, combining theory and practice, with well-structured chapters followed by practical projects that ensure an immersive experience. It aims to empower students to leverage AI's potential in an ever-evolving job market, emphasizing the importance of extracting insights and automating processes as a critical competitive advantage.
- Api GPT-3, GPT-4, Llama, BERT
- Prompt Engineering
- Fine Tuning, Transfer Learning and RAG
- LangChain, PEFT, LORA, QLORA
- Vector Databases, VectorDB, ChromaDB
DEEP LEARNING FOR ARTIFICIAL INTELLIGENCE APPLICATIONS WITH PYTHON AND C++
October 2024
DSA - Data Science Academy
Course 1/4 of the Data Science Academy AI Engineer Training
This course is a comprehensive and advanced program in Artificial Intelligence (AI) and Deep Learning, designed to deliver cutting-edge knowledge and practical skills. It covers foundational AI concepts, neural networks, and advanced applications in fields like Computer Vision, Natural Language Processing, and Financial Analysis.
With 10 hands-on projects, it emphasizes practical learning, focusing on state-of-the-art tools such as the Transformers architecture and the Hugging Face platform. Its dual programming approach integrates Python’s versatility with C++’s high performance, ensuring adaptability for real-time applications and advanced model deployment.
The course also features a detailed case study on the safe use of ChatGPT and includes the creation of a Large Language Model (LLM) from scratch, providing a robust foundation for tackling modern AI challenges. It stands out as a versatile and forward-thinking learning resource.
With 10 hands-on projects, it emphasizes practical learning, focusing on state-of-the-art tools such as the Transformers architecture and the Hugging Face platform. Its dual programming approach integrates Python’s versatility with C++’s high performance, ensuring adaptability for real-time applications and advanced model deployment.
The course also features a detailed case study on the safe use of ChatGPT and includes the creation of a Large Language Model (LLM) from scratch, providing a robust foundation for tackling modern AI challenges. It stands out as a versatile and forward-thinking learning resource.
- Transformers Architecture
- Large Language Models (LLMs)
- Transfer Learning and Fine Tuning
- C++
DATA ANALYSIS WITH PYTHON
July 2023
DSA - Data Science Academy
Course 3/3 of the Data Science Academy Data Analyst Training
During the training students will acquire fundamental skills of a Data Analyst: how to handle missing values, how to clean and process data, how to perform descriptive statistical analysis, how to apply binarization and encoding of categorical variables, attribute engineering and much more.
SQL FOR DATA SCIENCE
May 2023
DSA - Data Science Academy
Course 1/3 of the Data Science Academy Data Analyst Training
Course ranging from the most basic to advanced levels of SQL focused on solving data science problems.
DATA ENGINEERING WITH HADOOP AND SPARK
October 2022
DSA - Data Science Academy
Course 3/3 of Data Science Academy Data Scientist Training
This is a course focused on Data Engineering. Storing Big Data is a challenge, given its characteristics: data generated at high speed, high volume and great variety. This course teaches how to create a Hadoop cluster, how to configure a Hadoop cluster, how to apply mapping/reduction techniques on data. In addition, it also shows how to create a Data Hub with Hadoop and HBase and apply ETL to load Hadoop data. Topics involved: Hadoop, Cluster, ETL, Machine Learning, Spark, Amazon EMR, Data Mining.
MICROSOFT POWER BI FOR DATA SCIENCE, VERSION 2.0
September 2022
DSA - Data Science Academy
The course covers content related to Power BI in a very comprehensive way. It brings the construction of several interactive dashboards, connection and extraction of data from Relational and Non-Relational Databases, integration with Python and R programming languages. In addition, it brings an overview of the Microsoft Power Platform, with projects using Power BI Online, Power Apps, Power Automate and Power Virtual Agents.
- Introduction to Power BI
- Modeling, Relationship and DAX
- Cleaning, Transforming, Time Series, Aggregation and Filters
- Interactive Charts, Maps and Dashboards
- Fundamental statistics
- R language and Python
- Power Automate, Power Virtual Agents and Power Apps
DEPLOYING MACHINE LEARNING MODELS
July 2022
DSA - Data Science Academy
Course 3/4 of the Data Science Academy Machine Learning Engineer Training
This course is dedicated to Deploying Machine Learning models. The course covers AWS Cloud Environment, Google Cloud Platform and Azure and how to use AWS SageMaker to create an API for ML models. The deployment will be done with different tools for local or cloud consumption, such as TensorFlow, MLFlow, KubeFlow, MLeap, Spark MLLib and Scikit-Learn. Plus Keras, PyTorch and MxNet with Gluon, as well as Databricks, Docker and Streamlit. Flask and Django will also be covered in this course.
- AWS, GCP and Azure
- AWS SageMaker
- TensorFlow, MLFlow, KubeFlow
- MLeap, Spark MLLib, Scikit-Learning
- Keras, Pytorch, MXNet with Gluon
- Databricks, Docker and Streamlit
- Flask and Django
BUSINESS ANALYTICS WITH R AND PYTHON
July 2022
DSA - Data Science Academy
Data Science Academy Data Scientist Training Course 5/6
Business knowledge is one of the main skills of the Data Scientist. The objective of this course is to apply analytical techniques in business areas such as Marketing, Finance and HR, collecting data, defining metrics, creating models and extracting insights that generate value for companies and support decision-making.
- Predictive analytics
- Marketing Analytics
- RH Analytics
- Financial Analytics
- Social Network Analytics
PROFESSION DATA ANALYST
July 2022
EBAC - British School of the Creative Arts
Online course by the British School of Creative Arts and Technology teaching platform. The course covers everything from basics in Python to advanced topics in Machine Learning, Working in the Cloud, Big Data and Data Lake on AWS.
- Data Analysis
- Machine Learning
- SQL Language
- Data Visualization
- Work with Big Data
- Team Work with Git and Github
SOFT SKILLS - DEVELOPING BEHAVIORAL SKILLS
June 2022
DSA - Data Science Academy
Although technical knowledge is essential for anyone working with technology, behavioral skills can determine professional success. The course covers topics such as: Assertive Communication, Teamwork, Ownership & Accountability, Creativity, Agile Methodologies (SCRUM), Diversity and Multidisciplinary Teams.
Course available only for those who purchased any other paid course on the platform.
STATISTICAL ANALYSIS AND PREDICTIVE MODELING OF TIME SERIES
June 2022
DSA - Data Science Academy
This course aimed to present and exemplify in detail all the main concepts of Time Series. In addition, the main predictive modeling algorithms for this topic were covered, such as: ARIMA models, deep neural networks, libraries developed by the Facebook and Amazon team, and much more.
- Basic Concepts
- Checking Stationarity
- Smoothing
- ARMA, ARIMA, SARIMA models
- Facebook Prophet
- Deep Learning with LSTM
- Deep Learning with DeepAR
Course available only for those who purchased any other paid course on the platform.
DATA VISUALIZATION AND DASHBOARD DESIGN
June 2022
DSA - Data Science Academy
Data Science Academy Data Scientist Training Course 6/6
Data Science Academy Data Scientist Training Course. This is a course that teaches students to tell a story from data, using presentation techniques, design, dashboards and visualization strategies in various tools. Telling the story behind data is a skill that can be learned and practiced.
- Presentation Techniques
- Design Thinking
- Visual organization
- Dashboard and Charts
- View Tools
1ST BUSINESS GAMES TOURNAMENT - INOVA
April 2022
Inova Prudente
With the aim of encouraging the learning of business concepts, in addition to generating connections between participants, the Mayor's Office of Presidente Prudente, through the Inova Foundation, launched for the first time in the region, an edition of a Business Games Tournament.
The objective of the competition was to allow participants to simulate the management of a company in a highly competitive and interactive environment, making different business decisions based on news, reports and management charts.
BIG DATA REAL-TIME ANALYTICS WITH PYTHON AND SPARK
April 2022
DSA - Data Science Academy
Course 2/6 of the Data Science Academy Data Scientist Training
The objective of this course is to bring data analysis techniques, in batch and in real time, with two of the main tools used by Data Scientists: Python Language and Apache Spark.
- Introduction to Apache Spark
- Spark SQL
- Spark pair RDD, Accumulators and Broadcast
- Introduction to Spark Streaming
- Machine Learning algorithms using MLlib: Naive Bayes, Decision Tree, Random Forest, Regression, K-Means
- Creation of Recommendation Systems
Machine Learning
March 2022
DSA - Data Science Academy
Data Science Academy Data Scientist Training Course 4/6
The objective of this course is to bring the construction of Machine Learning models. In addition to studying machine learning theory, it is covered in practice how algorithms work in different projects.
- Features Engineering with Categorical Variables in Practice
- Algorithms: KNN, Naive Bayes, Linear Regression, Logistic Regression, XGB, SVM, Decision Trees
- Dimensionality Reduction with PCA
- Natural Language Processing
- TensorFlow and PyTorch for Deep Learning
- Deploying a Machine Learning model
DATA SCIENTIST TRAINING WITH PYTHON AND R [2022]
February 2022
Udemy
Complete course on Data Science. Creating predictive models with Deep Learning, RNNs and Time Series. Concepts of text mining, graphs, project management, NoSQL database, basic and advanced statistics and much more.
- Introduction to Python and R languages
- Cleaning, treatment and Exploratory Analysis of Data
- Graphics, Visualization and Dashboards
- Statistics I and II
- Linear Regression, Classification, Time Series
- Neural Networks and Deep Learning
- Graph Theory
- SQL and NoSQL
- Introduction to Spark with Databricks
TENSORFLOW: MACHINE LEARNING AND DEEP LEARNING WITH PYTHON
February 2022
Udemy
Learn in theory and practice how to build artificial neural networks to solve real everyday problems.
- Basic Syntax
- Regression and Classification
- Artificial, Convolutional and Recurrent Neural Networks
- Autoencoders
- Generative Adversarial Networks (GANs)
TENSORFLOW 2.0: A COMPLETE ABOUT THE NEW TENSORFLOW
December 2021
Udemy
A guide to the main features of Tensorflow 2.x. Implementations of Artificial Neural Networks, CNNs, Recurrent Neural Networks and other projects.
- Introduction to Tensorflow
- Artificial, Convolutional and Recurrent Neural Networks
- Transfer Learning and Fine Tuning
- Reinforcement Learning
- Tensorflow Lite
FACE AND OBJECT RECOGNITION WITH PYTHON AND DLIB
November 2021
Udemy
The course teaches how to detect faces using haarcascade, HOG and convolutional neural networks (CNN) techniques.
- Face detection with Haarcascade
- OpenCV
- HOG, KNN, Yalesface and SVM algorithms
- Dlib library
- Hog x CNN
PYTHON FUNDAMENTALS FOR DATA ANALYSIS
February 2021
DSA - Data Science Academy
This course covers the basic concepts and fundamentals of the Python programming language. In addition, the course covers the main Python libraries for data analysis and Data Science projects.
- Introduction to Python
- Main packages for analysis: Pandas, Numpy, Matplotlib, among others.
- Object Orientation
- Introduction to Tensorflow
- Introduction to Machine Learning
- Introduction to Deep Learning
- Web Scraping
BIG DATA FUNDAMENTALS 2.0
February 2020
DSA - Data Science Academy
The Big Data Fundamentals course theoretically addresses several concepts about Big Data, how it is used in the corporate environment and how it is impacting the world today.
GIT AND CONTRIBUTIONS TO OPEN SOURCE PROJECTS UDEMY
June 2019
Udemy
Course that covers from the most basic concepts to the most advanced about version control, tools like Git and GitHub, and how to contribute to Open Source projects.
COMPLETE WEB 2.0 DEVELOPMENT COURSE 2018 PYTHON AND DJANGO
April 2019
Udemy
The course addresses theoretical concepts about the Web, from the moment a user types the URL into the browser until the moment the site/system loads in the browser. The course brings several practical projects using the programming languages.
- Computer Network Theory
- HTML and CSS
- Javascript
- Python and Django