Development100% OFF

Data Science & AI Mastery: From Basics to Deployment

Udemy Instructor

4.3(10.4K students)

Self-paced

All Levels

About this course

“This course contains the use of artificial intelligence.”This comprehensive Data Science and Artificial Intelligence Mastery course is designed to take you from beginner to job-ready professional in just 100 days. Through a carefully structured curriculum, you’ll gain both theoretical knowledge and hands-on experience with the most in-demand tools and technologies in the industry.You’ll begin by building a strong foundation in data analysis, data cleaning, and feature engineering, learning how to work with structured and unstructured data. From there, you’ll dive deep into machine learning algorithms such as regression, classification, and clustering, while also mastering advanced topics like deep learning, neural networks, and generative AI.Every step of the way, you’ll reinforce your skills with hands-on labs, real-world case studies, and a capstone project that simulates industry challenges.

You’ll also explore data visualization, model deployment with APIs (FastAPI, Flask), and MLOps concepts like monitoring and drift detection, preparing you for the realities of production environments.By the end of this course, you’ll have a polished portfolio showcasing end-to-end AI projects, a deep understanding of tools such as Python, Pandas, Scikit-Learn, TensorFlow, PyTorch, Docker, and Streamlit, and the confidence to apply for roles like Data Scientist, Machine Learning Engineer, or AI Specialist.This isn’t just a course—it’s a complete career preparation journey, giving you the skills, projects, and confidence to stand out in today’s competitive data-driven job market.

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$90.99

Save $90.99 today!

Enroll Now - Free

Redirects to Udemy • Limited free enrollments

Share this course

https://freecourse.io/courses/data-science-ai-mastery-from-basics-to-deployment

“This course contains the use of artificial intelligence”The role of an AI Engineer has changed dramatically. In 2026, companies are no longer hiring people who can just train models or follow tutorials. They are hiring engineers who can build real AI systems, deploy them into production, reason about tradeoffs, and explain their decisions clearly in interviews.This course is designed to help you do exactly that.How to Land an AI Engineer Job in 2026 is a complete, end-to-end career roadmap that takes you from foundational skills to job-ready expertise. It combines core computer science, machine learning, deep learning, and modern GenAI systems with the practical skills needed to pass interviews and succeed on the job.You’ll start by building a strong foundation in Python programming, data science, mathematics, probability, and statistics—the skills every serious AI engineer is expected to know. From there, you’ll move into machine learning algorithms, feature engineering, model evaluation, and optimization, learning not just how models work, but why they work and when to use them.As the course progresses, you’ll dive deep into neural networks, deep learning, CNNs, RNNs, transformers, attention mechanisms, transfer learning, and fine-tuning. These sections go beyond theory, focusing on how modern AI models are actually used in real products and systems.What truly sets this course apart is its focus on modern AI engineering for 2026. You’ll learn how to build production-grade AI systems, including retrieval-augmented generation (RAG), agentic AI systems, autonomous workflows, and real-world deployment patterns. You’ll understand how AI systems fail, how to monitor them, how to evaluate model quality, and how to optimize for cost, latency, and reliability.This is not a “watch and forget” course. You’ll build hands-on projects every week, culminating in a portfolio of real AI systems you can confidently discuss in interviews. You’ll learn how to structure your GitHub projects, write strong READMEs, and turn technical work into compelling case studies that recruiters care about.The course also includes dedicated sections on AI engineer interviews and job preparation. You’ll learn how technical interviews are structured, how to approach coding questions, how to answer machine learning and deep learning theory questions, how to design AI systems on a whiteboard, and how to succeed in take-home assignments. You’ll also get guidance on resumes, LinkedIn positioning, networking strategies, and salary negotiation.By the end of this course, you won’t just “know AI.” You’ll be able to build, deploy, explain, and defend AI systems—the exact skills companies look for when hiring AI engineers in 2026.Whether you’re a student, software engineer, data scientist, or career switcher, this course gives you a clear, structured path to becoming job-ready and interview-confident in one of the most competitive roles in tech today.

Generative AI Engineering with OpenAI, Anthropic

Udemy Instructor

“This course contains the use of artificial intelligence”Step into the future of innovation with Generative AI Engineering: Build with OpenAI & Anthropic, a hands-on, lab-driven course designed to help you master the art and science of building real-world AI applications. Whether you’re a developer, data engineer, researcher, or AI enthusiast, this course equips you with the technical depth and practical experience to design, implement, and deploy intelligent systems powered by Large Language Models (LLMs) such as OpenAI’s GPT and Anthropic’s Claude.You’ll begin by uncovering how LLMs think, reason, and generate, then dive into the engineering foundations that power them — prompt engineering, context management, embeddings, and fine-tuning. Through immersive interactive labs, you’ll experiment with APIs from OpenAI, Anthropic, and Mistral, learning to control temperature, tokens, and reasoning depth to craft accurate, reliable, and domain-specific responses.Beyond theory, this course emphasizes real-world implementation through a full suite of 12 practical labs and 3 capstone projects: Labs 1–7 cover prompt chaining, API orchestration, latency benchmarking, and performance optimization. Labs 8–12 introduce advanced reasoning (Chain-of-Thought, self-reflection), safety guardrails, and deployment monitoring. Projects 1–3 guide you in building a Travel Itinerary Copilot, a Code Review Assistant, and a Knowledge-Aware RAG Copilot with real-time tool integration.You’ll also explore multi-model orchestration, cost-efficient hybrid pipelines, and secure deployment using frameworks like FastAPI, Flask, Streamlit, and React — transforming abstract AI capabilities into production-grade applications.By the end of this course, you’ll possess a complete Generative AI engineering toolkit — spanning LLM design, evaluation, safety, and scaling — empowering you to turn innovative ideas into deployable, intelligent products.Become a Generative AI Engineer who bridges imagination with implementation, building the next generation of smart, human-centered AI systems.

Machine Learning & AI Foundations Course

Udemy Instructor

"This course contains the use of artificial intelligence in creating scripts, visuals, audio, and supporting content"Are you ready to explore the world of Artificial Intelligence (AI) and Machine Learning (ML)? This beginner-friendly course will give you the foundational knowledge and practical skills to understand, apply, and evaluate AI systems with confidence.In this course, you’ll start by learning what AI is, its history and evolution, and how it is transforming industries such as healthcare, finance, education, and transportation. You’ll gain a solid understanding of core concepts like supervised learning, unsupervised learning, and reinforcement learning, along with the mathematics that make AI work—linear algebra, probability, and optimization.Next, you’ll dive into machine learning models and learn how to build and evaluate them using Python libraries such as NumPy, Pandas, and Scikit-learn. You’ll also explore the basics of deep learning, including neural networks, CNNs, and RNNs, and discover how they power applications like image recognition and natural language processing.Beyond the technical side, this course emphasizes the importance of ethical AI. You’ll learn about bias, fairness, accountability, privacy, and security, ensuring that you can think critically about the impact of AI in society.By the end of this course, you’ll have the confidence to understand and explain AI concepts, build simple ML models, and take the next step toward becoming a data scientist, ML engineer, or AI professional.Take your first step into the exciting world of Machine Learning and Artificial Intelligence today!

4.3•15.3K•Self-paced

FREE$86.99

Enroll

Data Science & AI Mastery: From Basics to Deployment

About this course

Skills you'll gain

Available Coupons