CERTIFICATES

Description: Explore deep learning with PyTorch, build models for real-world problems, and master advanced architectures like Transformers.

Description: Learn AI engineering, master APIs, LLMs, and build production-ready AI systems.

Description: Become an AI Engineer: Master AI development, deployment, and MLOps with hands-on Python, LLMs, and LangChain experience.

Description: Become a machine learning engineer with MLOps, model deployment, and real-world projects.

Description: Learn Keras, neural networks, and deep learning to solve real-world challenges like predicting housing prices.

Description: Master machine learning with Python using scikit-learn, PyTorch, and Gymnasium for supervised, unsupervised, deep, and reinforcement learning.

Description: Learn to build LLMs with PyTorch, transformers, and Hugging Face, from inception to real-world deployment.

Description: Learn to use the OpenAI API in Python for chatbots, semantic search, recommendations, advanced prompting, and embeddings.

Description: Learn MLOps fundamentals, deploy and monitor Python models with MLflow and DVC in a hands‑on production‑ready track.

Description: Learn Python NLP to process unstructured data, using NLTK, spaCy, scikit‑learn, and SpeechRecognition for transcription and sentiment analysis.

Description: Learn NLP: transcribe audio, analyze sentiment, and extract insights from Wikipedia, reviews, and flight data using NLTK, scikit‑learn, spaCy, SpeechRecognition.

Description: Learn RL fundamentals, apply Q‑learning, SARSA, deep RL, and RLHF using Python and Gymnasium for games, robotics, and trading.

Description: Learn to run, fine‑tune, and deploy Llama 3 for inference, summarization, and generation on consumer hardware.

Description: Advanced Python: context managers, decorators, testing, OOP, and best‑practice modular development.

Description: Learn LangChain to build LLM apps: chatbots, RAG, and autonomous agents using Hugging Face and OpenAI.

Description: Comprehensive Python track teaches ML fundamentals, advanced techniques, real projects, preparing you for machine‑learning scientist roles.

Description: Comprehensive beginner track teaches Python fundamentals, advanced concepts, and real‑world projects to launch a software development career.

Description: Advanced Python track: testing, optimization, packaging, Git, web scraping, OOP, data structures, algorithms for professional development.

Description: Learn Python basics, work with data types, built‑ins, modules, then build a user‑registration project.

Description: Learn Python basics: dates, times, time zones, string manipulation, regex, and classic algorithms with complexity analysis.

Description: Comprehensive Git course covering basics, branching, merging, rebasing, LFS, bisect, submodules, and collaborative workflows.

Description: Learn Python fundamentals, consume APIs, then build fast, async FastAPI services, culminating in a real‑time exchange‑rate API.

Description: Learn Excel, SQL, Tableau for data analysis; build a portfolio with a popular‑movies dataset, created with OpenEDG Python Institute.

Description: Learn Python fundamentals, build projects, and prepare for PCEP certification for diverse tech careers.

Description: Advanced Python course covering OOP, portfolio projects, and PCAP certification prep, for learners with basics.

Description: Learn JavaScript front‑end development, earn JSE entry‑level certification, no experience needed, boost career in web, mobile, gaming.

Description: Learn MCP to connect Claude with services: build servers/clients, expose tools, resources, prompts, and create a document‑management system.

Description: Learn MCP to connect Claude with services: build servers/clients, expose tools, resources, prompts, and create a document‑management system.

Description: Learn NN, MLP, CNN for image classification/segmentation and train a custom CNN on your dataset.

Description: Free OpenCV course teaches image/video manipulation, object and face detection for AI and deep learning.

Description: Learn essential Python to launch a career in computer vision, deep learning, and AI.

Description: Free VLM course teaches CLIP embeddings for zero‑shot classification, then Qwen2.5‑VL for image captioning and object detection hands-on.

Description: Free PyTorch bootcamp teaching deep‑learning fundamentals, hands‑on tensors, neural networks, optimization, plus object detection and segmentation.

Description: Learn TensorFlow to build neural networks, covering NLP, reinforcement learning, and deep, recurrent, convolutional architectures.

Description: Intro to analytics fundamentals, covering types, 5 V's, challenges, and AWS service mapping; 2‑hour, fundamental level.

Description: SageMaker course covers LLM data ingestion, distributed training, alignment, and optimized deployment.

Description: Advanced Spark RDD course covering architecture, caching, and advanced API operations.

Description: Deep TensorFlow course teaches neural nets, backpropagation, and architectures for images, sound, and text.

Description: SystemML lets you write R/Python-style ML code that auto-optimizes and scales from single-node to Hadoop/Spark clusters.

Description: Apache Kafka fundamentals, architecture, and real‑world use cases, plus hands‑on production/consumption, Spark integration, and Kafka Connect.

Description: A free crash‑course covering deep learning basics, CNNs, their power, and applications to jump‑start a data‑science career.

Description: Microsoft Learn offers browser‑based, interactive Jupyter notebooks covering basic ML models, EDA, and custom architectures as a foundation for deep learning.

Description: Generative AI apps on Azure AI Foundry require AI basics, Azure services knowledge, and programming skills.

Description: AI fundamentals and Azure AI services; requires Azure portal familiarity.

Description: Overview of adopting, using, and building AI copilots on Azure.

Description: Core AI concepts and Azure AI services overview.

Description: Intro to AI fundamentals and Azure AI services; requires Azure portal familiarity.

Description: Core AI concepts and Azure AI services overview.

Description: Core AI concepts and Azure AI services overview.

Description: Get started with Python, if you have no coding experience.

Description: Learn the most important language for data science.

Description: Learn the core ideas in machine learning, and build your first models.

Description: Solve short hands-on challenges to perfect your data manipulation skills.

Description: Handle missing values, non-numeric values, data leakage, and more.

Description: Better features make better models. Discover how to get the most out of your data.

Description: Use TensorFlow and Keras to build and train neural networks for structured data.

Description: Build convolutional neural networks with TensorFlow and Keras.

Description: Build convolutional neural networks with TensorFlow and Keras.

Description: Master efficient workflows for cleaning real-world, messy data.

Description: Explore practical tools to guide the moral design of AI systems.

Description: Extract human-understandable insights from any model.