Agentic AI, ML: Automate with Apps Script, n8n & Make

Discover the fundamentals of artificial intelligence, including machine learning, deep learning, generative AI, and natural language processing, and explore supervised, unsupervised, and reinforcement learning through practical pipelines.

Explore the machine learning pipeline from data collection and transformation to feature extraction, data splitting, training, evaluation with accuracy, precision, recall, F1, and deployment as an API or local service.

Master supervised learning with labeled input data that trains models to predict classes, using regression and classification with algorithms like decision trees, linear regression, random forest, and k-nearest neighbors.

Explore reinforcement learning where a model learns by trial and error through rewards, training thousands of iterations. The course covers deep Q-learning and Q-learning with a notebook demo.

Explore unsupervised learning with unlabeled data, including clustering methods like k-means and density-based approaches, and dimensionality reduction using principal component analysis, with a demo.

Explore natural language processing fundamentals, including text processing, data cleaning, stopword removal, and sentiment analysis; apply embeddings and deep learning to NLP tasks like text classification and text clustering.

Apply a complete machine learning pipeline from raw data to model deployment: data import, transformation with one-hot encoding, feature selection, train-test split, random forest training, evaluation, and deployment considerations.

Explore unsupervised learning with k-means clustering on a customer dataset and determine optimal clusters using the elbow method. Apply standard scaler and PCA for dimensionality reduction and clearer clustering.

Define automation and explain why it’s exploding, then outline fundamentals for building AI and automation workflows and compare no-code tools like Google Apps Script, Make.com, n8n, and Zapier.

Benchmark four automation tools—Make.com, Zapier, n8n, and Google Apps Script—to reveal cloud versus self-hosted hosting, visual editors, AI support, and pricing implications for scalable workflow design.

Benchmark four automation tools: Make.com, Zapier, n8n, and Google Apps Script, exploring cloud versus self-hosted hosting, visual editors, AI support, and practical use case comparisons.

Identify the best automation approach for web scraping, keyword filtering, and notifications using n8n, make.com, and Google Apps Script.

Learn Google Apps Script, a cloud-based scripting language built on JavaScript, to automate Google Docs, Sheets, and Gmail, process data, and integrate with calendars and external APIs.

Learn to use the google apps script editor to create your first automation, set time-based triggers, and test email workflows with JavaScript and chatgpt.

Automate email replies by using Google Apps Script with ChatGPT via the OpenAI API to read, filter by sender and subject, generate responses, and send replies.

Build a Google Apps Script workflow to create a Google Form, capture responses in a sheet, and reply to inquiries via ChatGPT powered by OpenAI.

Explore Make.com through an editor demo, learn to create accounts, projects, scenarios, and modules, and build autosave Gmail attachments with OpenAI Gemini integration for social media.

Explore the Make.com interface, learning to create and manage scenarios with triggers, actions, conditions, and outputs, and build AI-powered workflows like auto-saving Gmail attachments to Google Drive.

Build a Make.com scenario that saves Gmail attachments to Google Drive and logs sender, date, subject, and file name to Google Sheets for easy tracking.

Explore the open-source automation platform n8n, install it on a local server, and build scenarios linking Google Drive, Google Sheets, Facebook, and WhatsApp for personalized auto email responses via OpenAI.

Explore how to build an automation workflow by choosing a trigger, adding actions like reading emails or saving to Google Sheets, applying conditions, and generating outputs within the editor.

Learn how to set up and connect triggers and actions in a workflow automation platform, including creating credentials, choosing triggers like manual or form submissions, and integrating Gmail and OpenAI.

Explore prompt engineering and the autonomy of good prompts; assess AI model risks and learn advanced prompt techniques and templates to avoid hallucination, math errors, and prompt hacking.

Learn how to design prompt templates for AI workflows, including normal prompts, system-user chat templates, and message placeholders, for ChatGPT and other LLMs in Make.com and Google Apps Script.

Compare zero-shot and few-shot prompts, chain-of-thought reasoning, and program aided language to tackle complex prompts. Explore multi-prompt and multi-model techniques for classification and majority voting.

Discover the four pillars of responsible AI—fairness, privacy and security, transparency, and accountability—and the three questions: is it fair, is it safe, is it useful, to guide ethical automation.

AI reshapes the job market, creating roles like ai engineer and data scientist while enabling upskilling and automation platforms, including generative ai, for faster, more productive workflows.

Explore ai automation careers and learning paths, from prompt engineering to ai workflow automation, using make.com and google apps script, and advance from fundamentals to expert level.

Explore Kaggle datasets to train supervised and unsupervised models, automate emails with Google Apps Script and OpenAI, and build Make.com workflows connecting Facebook through prompt engineering and automation basics.

Reflect on ai fundamentals, automation basics, and tool demos (Google Apps Script, Make.com, n8n), then apply prompt engineering to your own use cases.

Apply course lessons to automate tasks with Apps Script, n8n, and Make.com, and build a 24/7 chatbot to support customers, saving time and boosting productivity.