No-Code Data Science and Machine Learning

Edureka via Coursera Specialization

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Provider

Coursera Specialization
Pricing

Paid Course
Languages

English
Certificate

Certificate Available
Duration & workload

8 weeks, 5 hours a week

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Overview

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This specialization is designed to give you a complete, structured pathway to master data science and machine learning — from building no-code data pipelines in KNIME to training visual ML models in Orange to deploying AutoML solutions on Google Vertex AI. Each course is built around step-by-step instructor video demonstrations that you follow along on your own setup — pausing, replaying, and practicing every technique at your own pace across three project-driven courses: Build Your First No-Code Data Workflow: Collect, clean, transform, and explore data using KNIME Analytics Platform. Applied Machine Learning Without Coding: Build, evaluate, and tune regression and classification models visually using Orange Data Mining. AutoML: Build ML Models without Code: Train, deploy, and monitor production-ready ML models for structured data, vision, and NLP using Google Vertex AI. By the end of this specialization, you'll design complete no-code ML pipelines, evaluate predictive models, deploy cloud-based predictions, and integrate ML outputs into real business tools — all without writing a single line of code.

Syllabus

Course 1: Build Your First No-Code Data Workflow
Course 2: Applied Machine Learning Without Coding
Course 3: AutoML: Build ML Models without Code

Courses

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8 hours 7 minutes
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Cloud-powered machine learning is now within reach for every data professional. This course teaches you to train, deploy, and monitor production-ready ML models using Google Vertex AI's AutoML platform — covering structured data, images, and text — entirely through the web console with no coding required. Throughout this course, you'll move through the complete AutoML lifecycle: platform setup, dataset management, advanced model training across vision and NLP domains, real-world deployment, and business tool integration — all backed by step-by-step video demonstrations on Google Cloud. You're expected to set up your own Google Cloud account, follow along with each instructor demonstration in the console, and pause the video as needed to complete each configuration or training step at your own pace. By the end of this course, you'll be able to: - Configure Google Cloud Platform and Vertex AI to set up and manage AutoML workflows for structured, image, and text datasets. - Train classification and regression models using AutoML Tables and interpret automated feature engineering and model evaluation results. - Build and evaluate AutoML Vision and Natural Language models for image classification, object detection, and text sentiment analysis. - Deploy trained models for online predictions, integrate outputs with Google Sheets and BigQuery, and monitor model performance through the cloud console. This course is designed for a diverse audience: data analysts, business intelligence professionals, product managers, domain experts, and non-technical professionals looking to leverage cloud ML capabilities to automate predictions and integrate AI into business workflows. Basic familiarity with data and machine learning concept, is recommended before enrolling. Step into cloud-powered ML and master the skills to build, deploy, and manage intelligent AutoML models that deliver measurable business impact — without writing a single line of code.
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9 hours 52 minutes
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Data science doesn't require code anymore. This course equips you with the practical skills to collect, clean, transform, and explore data using KNIME Analytics Platform — one of the world's most widely used no-code data science tools — so you can start building real workflows from day one. Throughout this course, you'll explore the full data science lifecycle and discover how no-code platforms are transforming the way analysts, business professionals, and domain experts work with data at scale. Each concept is reinforced through step-by-step video demonstrations that you can follow along on your own KNIME setup — pause, rewind, and practice at your own pace. By the end of this course, you'll be able to: - Navigate the KNIME interface and build end-to-end no-code data workflows from scratch. - Collect and integrate data from CSV, Excel, JSON, XML, databases, APIs, and web scraping sources. - Clean, transform, and validate data using normalization, encoding, aggregation, and feature engineering techniques. - Perform exploratory data analysis using descriptive statistics, visualizations, correlation matrices, and heatmaps in KNIME. This course is designed for a diverse audience: aspiring data analysts, business analysts, operations and marketing professionals, students entering data science, and anyone looking to gain practical data skills without programming knowledge. Prior familiarity with spreadsheet tools like Excel is helpful, though no technical or coding background is required to succeed in this course. Take the first step toward no-code data mastery and build the foundational skills needed to work confidently with real-world data using KNIME.