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AI & Machine Learning Bootcamp: 21 Courses in 1 (Python, DS)

Creative Online School

4.5(158 students)

Self-paced

All Levels

About this course

AI & Machine Learning Bootcamp: 21 Courses in 1 (Python, Data Science) is a complete, hands-on training program designed to take you from Python fundamentals to building and deploying real-world, production-ready AI applications.This course follows an end-to-end, full-stack AI approach. You won’t just learn how to analyze data or train machine learning models—you’ll learn how to turn data into intelligent systems, expose models through APIs, and integrate them into real applications the way professionals do in the industry.Whether you want to become a Data Scientist, Machine Learning Engineer, AI Engineer, or Full-Stack AI Developer, this bootcamp gives you the practical skills, mindset, and experience needed to succeed.Who This Course Is ForThis bootcamp is ideal for:Beginners who want to start a career in Data Science and AIPython developers moving into Machine Learning & AIData analysts upgrading to AI-driven rolesSoftware engineers building AI-powered applicationsStudents and professionals preparing for real-world AI jobsNo prior experience in AI or machine learning is required. Everything is taught step by step with clear explanations and practical examples.What Makes This Bootcamp DifferentMost courses focus only on theory or isolated tools.

This bootcamp teaches you the entire AI pipeline, including:Working with real-world, messy datasetsPerforming data analysis and feature engineeringTraining and evaluating machine learning modelsUnderstanding core AI and ML concepts clearlyConverting models into APIs and applicationsLearning production, deployment, and best practicesYou will think and work like a professional AI engineer, not just a student.What You Will LearnPython for Data ScienceMaster Python fundamentals tailored specifically for data science and AI, including clean coding practices, project structure, and debugging.Data Analysis & ManipulationWork with NumPy and Pandas to clean data, handle missing values, engineer features, and perform exploratory data analysis (EDA).Data VisualizationCreate meaningful visualizations using Matplotlib and Seaborn to communicate insights and uncover patterns in data.Statistics for Machine LearningLearn practical statistics needed for AI, including probability, distributions, correlation, hypothesis testing, and evaluation metrics—explained intuitively.Machine Learning with PythonBuild supervised and unsupervised models using scikit-learn. Learn regression, classification, clustering, model validation, and hyperparameter tuning.Real-World ML ProjectsApply your skills to practical projects that mirror real industry use cases, helping you build a strong portfolio.AI & Deep Learning FoundationsUnderstand how neural networks work, when to use ML vs AI, model complexity, overfitting, and responsible AI principles.Full-Stack AI DevelopmentLearn how to turn trained models into APIs, integrate them into backend systems, and connect AI with real applications.Deployment & Production BasicsUnderstand how AI models are saved, loaded, deployed, monitored, and maintained in real environments.Best Practices & SecurityLearn clean coding, data safety, performance optimization, and secure AI development techniques.Capstone ProjectsBy the end of the course, you will complete end-to-end capstone projects that demonstrate:Data preprocessing and analysisModel training and evaluationAPI integrationDeployment-ready AI workflowsThese projects are portfolio-ready and suitable for job applications, freelancing, or startup ideas.Career OutcomesAfter completing this bootcamp, you will be able to:Build real-world AI and machine learning applicationsWork confidently with data and ML pipelinesApply for Data Scientist, ML Engineer, or AI Developer rolesContinue advanced AI learning with strong foundations

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Level: All Levels

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Duration: Self-paced

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Instructor: Creative Online School

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🎓Certificate of completion
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Want to become an Successful Data Scientist but don’t know what to do and how?Take a look at this course where you willNot only learn responsibilities, qualifications, all the knowledge and tools required in detail to become a Successful Data Scientist including Data Analysis and Exploration, Model Development, Feature Engineering, Data Visualization, Collaboration, Experimentation, Continuous Learning and Documentation but alsoThe roadmap for becoming a Successful Data Scientist Preview many lectures for free to see the content for yourselfGet Udemy’s 30 days Money Back GuaranteeEnroll for free in my any other course using the coupon link in my YouTube channel videos from time to time subject to availabilityMy exposure to Data Analysis started 40 years back in 1979-81 at Indian Institute of Management Bangalore when I learnt about various methodologies and tools like Multivariate and Conjoint Analysis to make better management decisions. Data Science was not yet born as it has developed and matured now with developments in Machine Learning and other Algorithms that have made it possible to use those methodologies and toolsWhile I continued to use the Data Analysis during next about 30 years while working in Unilever, Johnson and Johnson and Danone, I came to know about the fully developed Data Science in 2016 when I started working at IIM Udaipur teaching and coaching MBA studentsDuring past 8 years, I have researched and learnt a lot more about the capabilities of Data Science to help all of us make better decisionsI bring in this course my learnings from this journey and share with you how can you also become an Successful Data Scientist and join this attractive and growing fieldLook at what other students saying about this course"It's been super amazing so far, I know it will get better and better""The course is amazing and worth the money""One of the finest courses by a professor on Udemy""Great stuff, am learning a lot through this""Great explanation, simple and precise""Great""As a sophomore in college who aspires to major in data science, this course is a really good overview of what I will need to do and to know. I am also impressed at how fast Mr. Singhal responded to my questions. This course goes in depth with everything and does a good job of limiting the assumptions of what we already know.""Amazing""Awesome: detailed, not too fast, proper use of visualization that enhanced concentration and understanding of the class.""Really a great lecture. Hope I might get my apprenticeship in Google. Thank you""Very well taught!""Very important information concerning data scientist career""very good and simple explanations""it is a good lecture and refreshing time of adding value to my data analysis package with more insightful points""I am impressed. The video was easy to watch. No stress at all""nice and informative lectures""i can able study practical level of knowledge of all"Preview for yourself many lectures free. If you like the content, enroll for the course, enjoy and skill yourself to Become a Successful Data Scientist. If don't like the content, please message about how can we modify it to meet your expectations.

2 Week Prompt Engineering Certification

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This course contains the use of artificial intelligence.The 2 Week Prompt Engineering Certification is designed to help learners master one of the most important skills in the age of Generative AI: knowing how to communicate clearly, strategically, and effectively with Large Language Models. Whether you use tools like ChatGPT, Claude, Gemini, Copilot, or AI-powered workplace platforms, the quality of your results depends heavily on the quality of your prompts.This course begins by explaining how LLMs actually work without unnecessary hype or technical confusion. You will learn the basics of tokens, probabilities, model behavior, and why small changes in wording can dramatically affect AI output. Instead of treating AI like magic, you will understand how to guide it with structure, context, examples, and constraints.In Week 1, you will build a strong foundation in prompt engineering fundamentals. You will learn the anatomy of a great prompt, including role, task, context, format, tone, length, and output requirements. You will practice turning vague requests into clear, structured instructions that produce more useful responses. The course also introduces core prompt patterns such as zero-shot prompting, few-shot prompting, instruction-based prompting, reusable templates, and structured output design.You will also learn how to control output quality by setting expectations for tone, format, detail level, audience, and constraints. When prompts fail, you will learn how to debug them using practical iteration frameworks. Through before-and-after examples, you will see how weak prompts can be transformed into high-performing prompts. The Week 1 lab, Prompt Makeover Sprint, gives you hands-on practice improving messy prompts and producing stronger AI outputs.In Week 2, the course moves into advanced techniques and real-world applications. You will explore reasoning prompts, step-by-step thinking structures, and when reasoning-based prompting is useful or risky. You will learn how to use role-based prompting and persona prompting to guide AI as an analyst, executive, teacher, engineer, researcher, or creative partner.The course also shows how to prompt for different tasks, including writing, coding, research, summarization, brainstorming, planning, and workflow support. You will learn how to create reusable prompt templates and build prompt-driven workflows that save time across repeated tasks. By the end of the course, you will understand how to combine multiple prompts into practical AI systems for real workplace use.The final lab, Build Your Prompt OS, helps you create a reusable personal or professional prompt system that can support your daily work. You will leave with a practical toolkit of prompts, templates, frameworks, and workflows that you can immediately apply to business, content creation, learning, coding, research, productivity, and automation.By completing this certification, you will gain the confidence to use AI tools more effectively, reduce poor outputs, improve productivity, and build a repeatable process for getting high-quality results from modern Generative AI systems.

4-Week AI Agents & Agentic Workflows Certification

Udemy Instructor

This course contains the use of artificial intelligence.The 4-Week AI Agents & Agentic Workflows Certification is a hands-on, practical program designed to help you move beyond basic prompting and learn how to build real AI agent systems that can reason, take action, use tools, remember information, retrieve knowledge, and coordinate with other agents.Most people use AI by typing prompts into a chatbot. But modern AI development is quickly moving toward agentic systems — AI-powered workflows that can break down tasks, make decisions, call external tools, use APIs, search knowledge bases, and complete multi-step processes. This course teaches you how those systems work and how to design them from the ground up.In Week 1, you will begin with the fundamentals of AI agents. You will learn the difference between simple LLM usage and a true agent system. You will explore the core anatomy of an agent, including input, reasoning, action, and output. You will also learn the popular Think → Act → Observe loop and understand how the ReAct pattern helps agents work through tasks step by step. By the end of the week, you will design and build your first working single-agent system.In Week 2, you will expand your agent with tools, memory, and RAG. You will learn why memory matters, how stateless agents differ from stateful agents, and how short-term and long-term memory improve agent behavior. You will also understand the basics of embeddings, vector databases, and vector search. Then you will learn how Retrieval-Augmented Generation helps agents produce more accurate, grounded, and context-aware responses. The weekly lab guides you through building a working RAG agent that can use external knowledge.In Week 3, you will move into multi-agent systems. You will learn when one agent is not enough and how multiple agents can work together through specialized roles such as Planner, Executor, Reviewer, and Manager–Worker patterns. You will explore agent communication, workflow coordination, orchestration tools like LangGraph, CrewAI, and AutoGen, and how to design systems that pass context between agents reliably. The weekly lab focuses on building a coordinated multi-agent workflow.In Week 4, you will bring everything together in a portfolio-ready capstone project. You will plan your architecture, build the core agent system, integrate tools, add memory, apply guardrails, validate outputs, and improve reliability. You will also learn the basics of observability, testing, debugging, performance optimization, and production thinking.By the end of this certification, you will have built practical agent systems and gained a clear understanding of how to design agentic workflows for real-world use cases across business, productivity, automation, research, operations, and enterprise AI.

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AI & Machine Learning Bootcamp: 21 Courses in 1 (Python, DS)

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