Development100% OFF

Applied DeepSeek AI: 25 Practical Projects for AI Developers

Udemy Instructor

0(13.7K students)

Self-paced

All Levels

About this course

Unlock the Power of DeepSeek AI with 25 Hands-On ProjectsAre you ready to build real-world AI applications using DeepSeek AI? This course is designed to take you from beginner to advanced AI developer, focusing on Natural Language Processing (NLP), chatbots, automation, and AI-driven applications—all without relying on cloud services! DeepSeek AI is an open-source, powerful AI model that enables developers to work with advanced AI automation, text generation, and NLP tasks locally.

In this course, you'll implement 25 real-world projects, gaining hands-on experience in applying AI to business, productivity, automation, and software development. What You’ll LearnBy the end of this course, you will be able to:- Set up and install DeepSeek AI on your local machine. - Build AI-powered text processing applications, including summarization, grammar correction, and sentiment analysis.

- Develop intelligent chatbots and virtual assistants for customer support, e-commerce, and personal productivity. - Automate everyday tasks with AI, such as email drafting, resume generation, and document summarization. - Implement AI-driven coding tools, including auto-completers, debuggers, and SQL generators.

- Optimize AI models for local performance and efficiency. - Develop AI applications for business use cases, such as financial analysis, job screening, and customer feedback processing. - Gain practical experience in NLP and AI-driven automation using Python.

- Work on real-world AI projects without relying on cloud-based APIs. Who is This Course For? This course is perfect for:- Python developers who want to integrate AI into their applications.

- AI & NLP beginners looking to gain hands-on experience. - Data scientists exploring AI models for text processing. - Tech professionals who want to build AI-powered automation tools.

- Entrepreneurs & startup founders interested in AI-driven applications. - Students & researchers working on AI projects without cloud dependencies. Whether you’re a beginner or an experienced AI developer, this course will provide real-world applications to enhance your AI skills.

Course Projects OverviewThis course includes 25 hands-on projects covering:- AI Text Processing – Summarization, sentiment analysis, and text generation. - Chatbots & Virtual Assistants – Building intelligent AI-driven assistants. - AI for Automation – Email responders, resume generators, and workflow automation.

- AI for Developers – Code auto-completers, debuggers, and API testers. - Business & Productivity AI – Financial analysis, job screening, and customer feedback processing. Each project is designed to help you apply DeepSeek AI to real-world use cases, making this course practical, hands-on, and beginner-friendly.

Why Take This Course? - Hands-on AI projects to build practical experience. - No cloud dependency – everything runs locally!

- Step-by-step implementation with complete code examples. - Covers AI automation, chatbots, NLP, and more! - Perfect for developers, students, and AI enthusiasts.

Start Building AI-Powered Applications Today! Join now and unlock the full potential of DeepSeek AI with 25 practical, real-world projects!

Skills you'll gain

Data ScienceEnglish

Available Coupons

Course Information

Level: All Levels

Suitable for learners at this level

Duration: Self-paced

Total course content

Instructor: Udemy Instructor

Expert course creator

This course includes:

📹Video lectures
📄Downloadable resources
📱Mobile & desktop access
🎓Certificate of completion
♾️Lifetime access

$0$95.99

Save $95.99 today!

Enroll Now - Free

Redirects to Udemy • Limited free enrollments

Share this course

https://freecourse.io/courses/deepseek-r1-real-world-projects

Disclaimer: This course contains the use of artificial intelligence(AI).Most data courses teach you Python syntax. This course teaches you how to think like a data analyst, work like a professional, and get hired like one. you will go from writing your first line of Python to deploying a complete data analytics project — with machine learning, AI-powered insights, interactive dashboards, and a GitHub portfolio that proves you can do the work.This is not a theory course. Every lecture has real data, real code, and real business decisions behind it.WHY THIS BOOTCAMP IS DIFFERENTEvery other Python for data course stops at the technical skills. This one goes further. You will learn how to use AI tools like the Anthropic API to analyze data 5x faster, how to communicate insights to executives using the SCQA framework, and how to position yourself for U.S. data analyst roles as an international professional navigating OPT, STEM OPT, and H-1B pathways.The skills in this course are not academic. They are the exact skills hiring managers test in data analyst interviews at U.S. companies right now.WHAT YOU WILL BUILDBy the end of this bootcamp you will have completed a full end-to-end analytics project . Your deliverables will include a clean, documented GitHub repository, a machine learning model that predicts high-value orders with over 80% accuracy, an interactive Plotly Dash dashboard your stakeholders can actually use, an AI-generated executive summary built with the Anthropic API, and an automated Python report that runs and emails itself on a schedule.That portfolio project is your most powerful job application tool. More credible than a certificate. More specific than a resume bullet.WHAT IS COVERED — DAY BY DAYFirst day covers Python foundations built specifically for data work. You will set up your environment, learn the only Python you actually need, and read your first real-world dataset.Day 2 covers data cleaning and wrangling with pandas. You will handle nulls, fix data types, remove duplicates, merge DataFrames, and build an analysis-ready dataset from scratch.Day 3 covers exploratory data analysis. You will apply descriptive statistics correctly, build professional visualizations with Matplotlib and Seaborn, and generate 10 business insights from a real e-commerce dataset without touching a single machine learning model.Day 4 covers AI-assisted analysis. You will make your first API call to a large language model, build a personal analyst assistant in Python, and master prompt engineering techniques specifically designed for data tasks.Day 5 covers machine learning fundamentals. You will build regression and classification models with scikit-learn, interpret every output in plain English, and evaluate your models correctly using cross-validation, confusion matrices, and F1 scores.Day 6 covers dashboards and data storytelling. You will build interactive dashboards with Plotly and Dash, structure analyst presentations using the SCQA framework, and automate a complete reporting pipeline that generates and emails a PDF report on a schedule.Last Day covers your capstone project and career positioning. You will complete a full end-to-end analytics project, publish it on GitHub with a recruiter-ready README, and build a 30-day job search action plan designed specifically for international professionals in the U.S. market.WHO THIS COURSE IS FORThis course is built for international students and professionals on F-1, OPT, or STEM OPT who want to transition into data roles in the U.S. It is also for working professionals in non-technical fields who want to upskill into analytics without a computer science background, and for early-career analysts who know the basics but have never built a complete portfolio project or integrated AI into their workflow.You do not need a mathematics degree. You do not need prior programming experience. You need a laptop, a willingness to write code alongside the lectures, and a goal to land a data role.REQUIREMENTSNo prior Python experience is required. A computer with internet access and at least 8GB of RAM is sufficient. All software used in this course is free and open source. API usage in the AI modules requires a free account — setup is covered in the lecture.A NOTE ON CAREER OUTCOMESData Analyst, Business Intelligence Analyst, Analytics Engineer, and Data Scientist roles are among the most consistent H-1B sponsoring positions in the U.S. market. All qualify for STEM OPT extension under the relevant CIP codes. This course does not just build your technical skills — it builds the portfolio evidence that makes your application stand out to employers who sponsor visas.Every skill in this bootcamp was chosen because it appears in job descriptions, gets tested in interviews, and transfers directly to your first week on the job.Enroll now. Your portfolio project starts in the first lecture.

AI Agents: From Foundations to Enterprise Systems

Udemy Instructor

Disclaimer: This course contains the use of artificial intelligence(AI).AI agents are rapidly transforming how software is built, decisions are made, and work gets done across industries. This course is a comprehensive, hands-on journey into designing, building, and deploying intelligent AI agents—from foundational concepts to enterprise-grade systems. Over 52 structured weeks, learners progress step by step through the full lifecycle of agentic AI without relying on a single capstone project, ensuring continuous, practical learning every week.You begin by mastering the core foundations of AI agents, including agent architectures, perception–action loops, reasoning, planning, and memory. Early modules focus on understanding how large language models power modern agents, how prompts differ from programs, and how agents decompose complex goals into executable tasks. Through guided labs, you build your first agents, add memory, enable tool usage, and implement structured reasoning patterns that go far beyond simple chatbots.As the course progresses, you move into agent frameworks, orchestration, and multi-agent collaboration. You learn how agents communicate, delegate tasks, resolve conflicts, and operate as coordinated systems rather than isolated components. Hands-on labs emphasize real execution—building sequential and parallel workflows, debugging agent failures, evaluating outputs, and optimizing for latency and cost. You gain practical experience designing agents that are reliable, explainable, and measurable.A major focus of the course is knowledge-driven and data-aware agents. You build retrieval-augmented agents, integrate structured and unstructured data sources, work with documents, and design long-term memory systems that persist and evolve over time. You also explore advanced capabilities such as multi-modal agents that reason across text, images, and audio, as well as real-time and event-driven agents that respond dynamically to changing inputs.The course then shifts into enterprise-grade agent systems. You learn how to secure agents, prevent prompt injection, enforce governance, and design human-in-the-loop workflows. Topics such as observability, monitoring, versioning, scaling, and cost optimization prepare you to deploy agents in production environments. Ethical considerations and responsible AI practices are woven throughout, ensuring agents are safe, transparent, and aligned with organizational policies.In the final phase, you apply agentic AI across real business domains including HR, finance, sales, IT operations, compliance, research, and personal productivity. Each week includes multiple topics, two hands-on labs, and a practical homework assignment, reinforcing skills through continuous application rather than a single end-of-course project.By the end of this course, learners will confidently design, build, deploy, and govern AI agents that operate autonomously, collaborate effectively, and deliver real business value—equipping them with future-ready skills for the rapidly evolving world of agentic AI.

AI in Healthcare: A-Z Guide on Tech, Applications & Ethics

Udemy Instructor

Are you ready to be part of the biggest transformation in the history of medicine?Artificial Intelligence is no longer a futuristic concept—it is reshaping healthcare right now. From diagnosing cancer earlier than humanly possible to discovering life-saving drugs in record time, AI is the new nervous system of modern medicine.Welcome to AI in Healthcare: A-Z Guide on Tech, Applications & Ethics, the most comprehensive, practical, and accessible guide.Whether you are a clinician, a healthcare administrator, a medical student, a Pharmacist, a Nurse, or a technologist, this course will strip away the hype and give you a deep, actionable understanding of how AI works, where it is applied, and the ethical challenges we must navigate.We focus on "Augmented Intelligence"—the vision where AI does not replace healthcare professionals, but elevates them, automating burnout-inducing tasks and providing superpowers in diagnostics and decision-making.What You Will Learn:Master the AI Toolkit: Understand the core technologies driving the revolution, including Machine Learning (ML), Deep Learning, Natural Language Processing (NLP), Computer Vision, and Medical Robotics.Revolutionize Diagnostics: Discover how Convolutional Neural Networks (CNNs) are acting as a radiologist’s co-pilot to detect cancer, diabetic retinopathy, and neurological disorders like Alzheimer's.Reinvent Drug Discovery: Learn how AI is solving the pharma R&D crisis by accelerating target identification, virtual screening, and clinical trials (featuring case studies like BenevolentAI).Personalize Medicine: Explore the "N-of-1" revolution, from AI-driven oncology treatment plans to precision robotic surgery with the da Vinci 5 system.Optimize Hospital Operations: See how Predictive Analytics and Ambient AI Scribes are tackling clinician burnout, managing patient flow, and automating clinical documentation.Navigate the "Implementation Hurdles": Understand the critical hurdles of HIPAA & Data Privacy, Algorithmic Bias, FDA Regulation, and EHR Interoperability.Master AI Ethics: Tackle the tough questions regarding the "Black Box" problem, Explainable AI (XAI), patient accountability, and informed consent.Future-Proof Your Career: Get a look at the 5-10 year horizon, including Generative AI, Synthetic Data, Federated Learning, and the rise of the Augmented Clinician.Course Curriculum Breakdown:Module 1: The Revolution Begins We define AI in a clinical context and explore the "Perfect Storm" driving this shift: the Data Deluge (Genomics, EHRs), Exponential Computing Power (GPUs), and the economic necessity of modern healthcare.Module 2: The Core Technologies No coding required! We break down complex tech into simple terms. You will understand Supervised vs. Unsupervised Learning, how Neural Networks mimic the brain, and how NLP unlocks the 80% of medical data trapped in doctors' notes.Module 3: AI in Diagnostics Dive into Radiology and Digital Pathology. We analyze how AI detects lung and breast cancer in CTs/MRIs, screens for blindness, and assists pathologists with tissue sample analysis. Spotlight: GE Healthcare, Aidoc, Paige AI.Module 4: Pharma & Drug Discovery See how AI cuts drug development timelines from years to months. We cover high-speed virtual screening, predicting drug toxicity, and optimizing clinical trials.Module 5: Personalized Medicine & Surgery Move beyond "one-size-fits-all." Learn how AI tailors oncology treatments based on your genome (Tempus case study) and provides "force feedback" and integrated intelligence in robotic surgery (Intuitive Surgical & Medtronic).Module 6: Hospital Operations Tackle the crisis of burnout. Learn how AI automates medical coding, creates optimized schedules, and uses predictive analytics to manage hospital bed capacity and patient flow.Module 7: Patient Engagement Shift from reactive to proactive care. Explore the "Digital Front Door," Remote Patient Monitoring (RPM) for chronic conditions (Diabetes, CVD), and 24/7 AI Chatbots for triage and mental health support.Module 8: The Implementation Gauntlet We take an honest look at the barriers: The risk of re-identification in data, the dangers of Algorithmic Bias in health equity, navigating FDA approval pathways (510(k) vs. De Novo), and the cost of integration.Module 9: The Moral Compass (Ethics) We tackle the "Black Box" problem—how can we trust an AI if we don't know how it thinks? We discuss the rise of Explainable AI (XAI), liability when AI makes a mistake, and the evolution of informed consent.Module 10: The Future Horizon (5-10 Years) Prepare for what’s next. We cover Generative AI for synthetic data creation, Federated Learning for privacy-preserving collaboration, and the essential need for "Algorithmic Literacy" in medical education.Join us today to bridge the gap between medicine and technology. Enroll now to become a leader in the era of Augmented Intelligence!

0.0•1.7K•Self-paced

FREE$96.99

Enroll

Applied DeepSeek AI: 25 Practical Projects for AI Developers

About this course

Skills you'll gain

Available Coupons

Course Information

This course includes:

Share this course

You May Also Like

Data Analytics with Python & AI

AI Agents: From Foundations to Enterprise Systems

AI in Healthcare: A-Z Guide on Tech, Applications & Ethics

Applied DeepSeek AI: 25 Practical Projects for AI Developers

About this course

Skills you'll gain

Available Coupons

Course Information

This course includes:

Share this course

You May Also Like

Data Analytics with Python & AI

AI Agents: From Foundations to Enterprise Systems

AI in Healthcare: A-Z Guide on Tech, Applications & Ethics