Update README.md

Author: DiogoRibeiro7

README.md

@@ -73,9 +73,45 @@ I'm a **veteran Data Scientist** with over two decades of experience, proudly ha
 
 ### 🛠️ **Technical Skills**
 
-- **Statistical Modeling in Management**: Expertise in survival analyses, cohort analysis, and production analysis and modeling.
-- **Optimization of Industrial Processes**: Ensuring efficiency and productivity through advanced optimization techniques.
-- **IoT & Automation**: Working with Raspberry Pi and sensors to explore applications in IoT, automation, and environmental monitoring, integrating hardware and software solutions for innovative projects.
+- **Programming Languages**:
+  - **Python**: Expertise in data manipulation, statistical modeling, and machine learning, using libraries such as Pandas, NumPy, SciPy, and Scikit-Learn.
+  - **SQL**: Proficient in writing complex queries for data extraction, manipulation, and analysis, with experience in optimizing queries for large datasets.
+  - **R**: Skilled in statistical analysis and data visualization, leveraging packages such as dplyr, ggplot2, and caret for specialized analytics in health and logistics.
+  - **Bash/Zsh Scripting**: Knowledgeable in scripting for automation tasks, particularly in data processing pipelines and deployment workflows.
+  - **Additional Languages**: Familiar with **Fortran**, **Ruby**, **Rust**, and **TypeScript** for specialized applications, including numerical methods, IoT, and web development.
+
+- **Data Science & Machine Learning Tools**:
+  - **Scikit-Learn** and **TensorFlow**: Experienced in developing and deploying machine learning models, including supervised and unsupervised learning for classification, regression, and clustering tasks.
+  - **XGBoost and LightGBM**: Specialized in gradient boosting methods for high-performance predictive modeling, particularly in structured datasets.
+  - **Time Series Analysis Libraries**: Proficient with **Statsmodels**, **Prophet**, and custom implementations in Python for forecasting and anomaly detection.
+  - **Visualization**: Expertise with **Matplotlib**, **Seaborn**, and **Plotly** for creating comprehensive visual reports that aid decision-making.
+
+- **Big Data and Real-Time Processing**:
+  - **Apache Flink** and **Apache Kafka**: Skilled in setting up real-time data streaming and analytics pipelines, especially for IoT and industrial applications.
+  - **Apache Iceberg**: Experience building a data lake house to manage big data efficiently, reducing costs and improving access and query performance.
+  - **Hadoop Ecosystem**: Familiarity with **HDFS** and **Spark** for handling large datasets and parallel processing, especially for batch processing in ETL pipelines.
+
+- **IoT & Automation**:
+  - **Raspberry Pi & Sensors**: Experience integrating hardware and software for IoT applications, automating data collection, and monitoring in logistics and environmental control.
+  - **Edge Computing and Embedded Systems**: Implementing data processing on edge devices for real-time insights, utilizing Python and C for embedded system applications.
+  - **MQTT and HTTP Protocols**: Knowledgeable in IoT protocols to manage sensor data flow, ensuring reliable and efficient communication between devices and analytics platforms.
+
+- **DevOps & Automation**:
+  - **GitHub Actions**: Proficient in developing CI/CD workflows for automated testing, deployment, and monitoring of machine learning and data processing pipelines.
+  - **Docker and Kubernetes**: Skilled in containerization and orchestration, facilitating scalable deployments of ML models and data processing systems.
+  - **Jenkins**: Experienced in setting up CI/CD pipelines for continuous integration, testing, and deployment.
+
+- **Database & Data Warehousing**:
+  - **PostgreSQL, MySQL, and DynamoDB**: Expertise in relational and NoSQL databases, proficient in database design, indexing, and query optimization.
+  - **Apache Iceberg**: Using Iceberg for data lake storage, allowing for efficient, schema-evolving, and real-time analytics solutions.
+  - **AWS S3 and Redshift**: Experience with cloud storage and data warehousing solutions, ensuring scalable data handling for analytics and machine learning applications.
+
+- **Statistical & Analytical Skills**:
+  - **Survival and Cohort Analysis**: Statistical modeling for understanding customer retention, product lifespan, and behavior over time.
+  - **Optimization**: Linear and nonlinear programming for optimizing industrial and supply chain processes.
+  - **Predictive Modeling and Forecasting**: Time-series analysis and demand forecasting in logistics, supply chain, and health.
+  - **Health Outcomes Modeling**: Experience developing models to analyze patient outcomes and healthcare intervention efficacy.
+
 
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