My Certificates

Prepare for the GitHub Foundations Certification by learning the fundamentals of Git and GitHub: version control, collaboration, and branching. Covers creating and modifying repos, issues, pull requests, GitHub Projects, Actions automation, administration, authentication, and advanced security features.

Comprehensive AI development track: master OpenAI API for text generation and multi-modal systems, prompt engineering with few-shot and chain-of-thought techniques, Hugging Face for open-source NLP models, AI ethics principles, embeddings for semantic search, and LangChain for building LLM applications.

Take your GitHub skills to the next level: dive deeper into GitHub Projects, automation with GitHub Actions, administration and authentication, InnerSource practices, and advanced security features for managing complex workflows and securing your codebase.

Comprehensive overview of AI ethics spanning industry, policy-making, and academia. Covers core principles of ethical AI including transparency, fairness, and accountability, strategies to minimize biases, explainable AI (XAI) techniques, and ethical frameworks for crafting responsible AI systems by design.

Navigate the Hugging Face Hub to load, use, and save pre-trained models and datasets for model training. Build text classification pipelines for grammatical correctness, summarize long passages using extractive and abstractive models, and create document Q&A pipelines to converse with documents.

Augment your LLM toolkit with LangChain: integrate OpenAI and Hugging Face models, build chatbots with prompt templates and few-shot strategies, create sequential chains using LCEL, develop agents with custom tools, and master RAG with document loaders, text splitters, and vector databases.

Designed for developers new to software engineering or experienced engineers exploring AI coding agents. Walks through installation, first prompts, the explore-plan-code-commit workflow, context management, CLAUDE.md customization, reusable skills, MCP database connections, and automated hooks.

Are you ready to start creating systems and applications using AI? Learn the OpenAI API in Python to build chatbots, semantic search engines, and recommendation systems. Master state-of-the-art prompting techniques and encode large text corpora for context-aware applications using embeddings.

Master the art of prompt engineering: craft specific prompts, design structured outputs, apply advanced strategies like few-shot, chain-of-thought, and self-consistency prompting. Solve real-world business problems including summarization, translation, ticket routing, code generation, and chatbot development.

Production-ready OpenAI API applications: structure end-to-end API calls with error handling and batching, use function calling to extract structured data and connect with external APIs, apply content moderation, mitigate prompt injection attacks, and implement safety best practices.

Unlock powerful AI applications through embeddings: represent text numerically to capture context and intent, build semantic search engines, recommendation systems, and sentiment analysis classifiers. Create embeddings using OpenAI models and use ChromaDB to store and query them in a vector database.

Navigate GitHub effectively: create public and private repositories, modify files, manage branches, create and review pull requests, clone and fork repos, generate Personal Access Tokens, assign tasks, and collaborate with team members on coding and data projects.

Data engineer responsibilities: understand core roles, how they differ from data scientists, and how they facilitate data flow through an organization. Learn data structures, SQL databases, data warehouses, data lakes, build and automate data pipelines, and apply parallel and cloud computing.

Build upon foundational Git knowledge with branches, remote repos, and merge conflicts. Discover how branches enable continuous development, learn essential branching techniques, resolve merge conflicts, and synchronize content between local and remote repos using clone, fetch, pull, and push.

Access AI models from the OpenAI API using Python: send requests to GPT models, generate and transform text content, perform sentiment analysis, categorization, and build AI-powered chatbots with conversation history, system messages, and multi-turn prompt strategies.

Develop multi-modal applications with OpenAI: master audio models for speech-to-text and text-to-speech in multiple languages, utilize content moderation models, and build an end-to-end customer service chatbot that receives voice queries, responds in the customer's native language, and provides AI-generated audio.

DataCamp certification in AI Fundamentals, covering core concepts of artificial intelligence and machine learning including neural networks, supervised and unsupervised learning, natural language processing, and practical AI applications across industries.

Git version control fundamentals: learn the benefits and fundamentals of version control, navigate the shell, create Git repositories, convert existing projects, stage and commit files, view and navigate repository history, compare versions, and revert changes.

Essential DevOps concepts for modern software development: distinguish between DevOps, DataOps, and MLOps, apply project management methodologies, understand software architecture and CI/CD pipelines, build and automate data pipelines, and ensure data quality, observability, and reliability.

Hands-on lab with GNS3 & Wireshark, covering TCP/IP, ARP, MAC, subnetting, and network diagnostics using ifconfig, ip, netstat, and arp.

Used Wireshark to analyze the TCP/IP layer of an HTTP request, including the physical WLAN layer information and the TCP and HTTP packets.

Learned to interpret, analyze, and communicate data insights effectively using visualization and storytelling. Covered data-driven decision-making, the four types of analytics (descriptive, diagnostic, predictive, prescriptive), and the DIKW process for transforming raw data into actionable wisdom.

Fundamentals of data types, structures, and decision-making. Learn about structured vs. unstructured data, the DIKW framework for data-driven decisions, data ethics and privacy, the data life cycle, and how to identify and avoid common data mistakes in organizations.

Introduction to MongoDB including CRUD operations, indexing, and data modeling.

Developed algorithmic problem-solving skills and learned to implement efficient algorithms in Python.

Comprehensive Linux training covering command line, shell scripting, and system administration.

Intensive summer program covering artificial intelligence fundamentals and applications.

Introduction to Python programming with interactive lessons and practical exercises.

Applied Python to data science workflows including data analysis and visualization.

Beginner level Italian language certification covering basic vocabulary and grammar.

Core Python concepts including OOP, file handling, and exception management.

Explored the interdisciplinary connections between mathematics and various scientific fields.

SQL database fundamentals including queries, joins, and data manipulation.

Mastered Git version control including branching, merging, and collaboration workflows.

Gained foundational knowledge of the Intel OpenVINO toolkit, covering inference flow, model optimization, and hardware acceleration for computer vision tasks.

Built a strong foundation in Git version control, covering branching, merging, rebasing, and collaborative workflows using GitHub and Bitbucket with both CLI and Sourcetree tools.

Completed training on designing and deploying Industrial IoT solutions using Google Cloud Platform. Covered IoT Core, Pub/Sub, Dataflow, BigQuery, and Dataprep for building scalable, secure data pipelines from devices to analytics. Included practical labs on streaming data ingestion, real-time analytics, and dashboard creation with Data Studio.

Explored how to plan and manage ML projects on Google Cloud, including assessing feasibility, defining data strategy, addressing bias, and aligning AI initiatives with business goals.

International Conference on Bioinformatics participation and research presentation.

Completed an in-depth exploration of human physiological systems, covering neural, cardiovascular, respiratory, endocrine, and renal functions. Gained understanding of homeostasis, body regulation, and system interdependencies through case-based analysis and virtual lab simulations.

Completed training on the epidemiology and transmission dynamics of SARS-CoV-2, with practical instruction on case investigation, contact tracing workflows, quarantine protocols, and ethical considerations in data privacy. Emphasized effective communication, public health intervention design, and mitigation strategies.

Advanced ML techniques including handling missing values, categorical variables, and pipelines.

Introduction to machine learning models including decision trees and random forests.

Advanced SQL queries including JOINs, window functions, and query optimization.

SQL fundamentals including SELECT statements, WHERE clauses, and basic aggregations.

Techniques for handling missing data, removing duplicates, and standardizing formats.

Working with geospatial data and creating interactive maps using GeoPandas and Folium.

Creating effective visualizations using seaborn and understanding visualization principles.

Mastering pandas DataFrame operations for data manipulation and analysis.

Python programming fundamentals including syntax, functions, and working with external libraries.

Completed intermediate-level training on applying AWS cloud services for machine learning workflows, including model development, training, and deployment using Amazon SageMaker. Covered computer vision (Amazon Rekognition, DeepLens), natural language processing (Comprehend, Translate, Transcribe), and MLOps automation with SageMaker Ground Truth and Neo.

Completed a project-based course on professional resume design and optimization. Covered resume structure, action-oriented writing, keyword integration for Applicant Tracking Systems (ATS), and peer-reviewed drafting techniques aligned with industry expectations.

Certified Network Security Specialist (CNSS) by the International CyberSecurity Institute (ICSI), with comprehensive training in cybersecurity fundamentals, encryption techniques, malware analysis, and industry best practices.

Practical machine learning implementations using Python and scikit-learn library.

Completed training in Psychological First Aid (PFA) using the RAPID model: Reflective listening, Assessment of needs, Prioritization, Intervention, and Disposition. Learned to provide mental health support in emergencies, triage crisis reactions, promote resilience, and practice self-care.

Creating compelling data visualizations using matplotlib, seaborn, and other Python libraries.

Data manipulation and analysis techniques using pandas and NumPy.

Completed a course covering essential mathematics for data science, including probability, statistics, linear algebra, functions, derivatives, exponents, logarithms, and Bayes’ theorem to prepare for advanced data science coursework.

Comprehensive Python bootcamp covering fundamentals to advanced topics with hands-on projects.

Covering supervised machine learning techniques, including linear and logistic regression, gradient descent, feature engineering, regularization, and model evaluation using Python, NumPy, scikit-learn and Matlab.

JavaScript programming from basics to DOM manipulation and asynchronous programming.

C programming fundamentals including pointers, memory management, and data structures.

Introduction to Python programming with focus on data science applications.

Learning the systematic approach to solving data science problems from problem definition to deployment.

Practical experience with Jupyter notebooks, RStudio, and other open-source data science tools.

Foundational concepts of data science including the role of data scientists and the data science workflow.

CSS styling techniques including layouts, animations, and responsive design.

HTML fundamentals for creating structured web pages with semantic markup.

C# programming including OOP principles and .NET framework basics.

C++ programming covering OOP, STL, and advanced language features.