Generative AI Mastery: From ChatGPT to LangChain in Python
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Unlock the future of Artificial Intelligence with “Generative AI Mastery: From ChatGPT to LangChain in Python”! This comprehensive course is designed to take you from a beginner to an advanced level in Generative AI, focusing on ChatGPT, LangChain, Prompt Engineering, and the latest Large Language Models (LLMs). Whether you are a data scientist, AI enthusiast, or software developer, this course equips you with the skills needed to build, deploy, and optimize Generative AI models and applications using Python.
What You Will Learn:
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Fundamentals of Generative AI: Understand the core concepts, architectures, and applications of Generative AI, including ChatGPT and other cutting-edge models.
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Prompt Engineering for ChatGPT: Master prompt design and optimization techniques to get the most accurate and efficient outputs from ChatGPT.
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Large Language Models (LLMs): Dive deep into LLMs, learning how to fine-tune and deploy them for real-world use cases.
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LangChain Integration: Learn how to leverage LangChain to build advanced AI-driven applications that utilize natural language processing and understanding.
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Python for Generative AI: Develop and implement AI models with Python. Utilize powerful libraries and frameworks to create scalable AI solutions.
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Building AI-Powered Applications: Learn end-to-end development, from data preprocessing and model training to deploying and monitoring AI models in production environments.
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Optimization Techniques: Discover strategies to optimize model performance, reduce latency, and enhance the quality of AI outputs for various applications.
Why Enroll in This Course?
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Hands-on Projects: Gain practical experience by working on real-world projects that will boost your portfolio and demonstrate your expertise in Generative AI.
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Expert Guidance: Learn from industry experts with years of experience in AI, Machine Learning, and Python development.
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Community Support: Join a vibrant community of AI learners and professionals to collaborate, share knowledge, and grow together.
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Stay Ahead in AI: As the field of Generative AI rapidly evolves, this course ensures you stay ahead with the latest trends, tools, and techniques.
Who Should Take This Course?
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Data Scientists and Machine Learning Engineers looking to specialize in Generative AI.
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Software Developers eager to build AI-powered applications using Python.
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AI Enthusiasts and Beginners who want to break into the AI field with a strong foundation in Generative AI technologies.
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Professionals and Students aiming to master ChatGPT, LLMs, Prompt Engineering, and LangChain.
Transform your career and become a sought-after expert in Generative AI. Enroll now and start your journey into the exciting world of AI innovation!
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5Introduction to Python - Essential Syntax and Semantics IVideo lesson
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6Introduction to Python - Essential Syntax and Semantics IIVideo lesson
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7Python VariablesVideo lesson
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8Operators in PythonVideo lesson
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9Python Basics: Variables, Operators, and Membership OperatorsQuiz
This test will cover basic concepts of variables, different types of operators (arithmetic, comparison, logical, bitwise, etc.), identity and membership operators, and a few common pitfalls in Python.
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10Python Basics - Variables, Operators, and MembershipQuiz
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14Python Lists and List Comprehension: Everything You Need to Know IVideo lesson
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15Python Lists and List Comprehension: Everything You Need to Know IIVideo lesson
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16Tuples in Python: Immutable CollectionsVideo lesson
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17Python Dictionaries: Efficient Key-Value Pair ManagementVideo lesson
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18Python Dictionaries: Efficient Key-Value Pair Management IIVideo lesson
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19Building a Simple Contact ManagerQuiz
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35Python Classes and ObjectsVideo lesson
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36Use of "self" in PythonVideo lesson
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37Encapsulation in PythonVideo lesson
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38Inheritance in PythonVideo lesson
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39Multiple and Multi-Level InheritanceVideo lesson
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40Polymorphism in PythonVideo lesson
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41*args and **kwargs in PythonVideo lesson
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42Abstraction in PythonVideo lesson
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46Road Map of NLP LearningVideo lesson
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47UseCases of the NLPVideo lesson
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48Tokenization Essentials and Key NLP TerminologiesVideo lesson
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49Practical Example of TokenizationVideo lesson
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50Text Preprocessing - StemmingVideo lesson
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51Text Preprocessing - LemmatizationVideo lesson
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52Parts of Speech (POS) Tagging Using NLTKVideo lesson
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53Text Preprocessing - StopWordsVideo lesson
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54Named Entity Recognition (NER)Video lesson
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55One-Hot Encoding in NLPVideo lesson
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56Example : One-Hot Encoding in NLPVideo lesson
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57Bag of Words (BoW) in NLPVideo lesson
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58Application of Bag of Words (BoW)Video lesson
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59What is N-GramVideo lesson
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60Predict the next word using an N-GramVideo lesson
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61TF-IDF in NLP and It's ApplicationVideo lesson
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62Identifying News Article Topics Using TF-IDFVideo lesson
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63Word Embedding in NLPVideo lesson
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