IIT Guwahati - Professional Certificate Program In Generative AI And Machine Learning
- Offered bySimplilearn
- Private Institute
- Estd. 2010
Professional Certificate Program In Generative AI And Machine Learning at Simplilearn Overview
Duration | 11 months |
Start from | Start Now |
Total fee | ₹1.35 Lakh |
Mode of learning | Online |
Official Website | Go to Website |
Credential | Certificate |
Professional Certificate Program In Generative AI And Machine Learning at Simplilearn Highlights
- Earn a certificate after completion of course.
- Fee can be paid in installments.
- Eligibility for a campus immersion program organized at IIT Guwahati.
Professional Certificate Program In Generative AI And Machine Learning at Simplilearn Course details
This program caters to working professionals from a variety of industries and backgrounds; the diversity of our students adds richness to class discussions and interactions.
- Generative AI
- Prompt Engineering
- Machine Learning Algorithms
- Supervised and Unsupervised Learning
- Model Training and Optimization
- Model Evaluation and Validation
- Ensemble Methods
- Deep Learning
- Natural Language Processing
- Computer Vision
- Reinforcement Learning
- Speech Recognition
- Statistics
The Generative AI and Machine Learning course enriches your career journey with comprehensive coverage of machine learning, deep learning, NLP, generative AI, reinforcement learning, computer vision, and more.
Combining theory with hands-on practice, it offers live virtual sessions, projects with integrated labs, and masterclasses by IIT Guwahati faculty.
This Generative AI and Machine Learning program guides you through essential programming concepts, practical data science, and advanced AI applications.
Professional Certificate Program In Generative AI And Machine Learning at Simplilearn Curriculum
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Embark on a comprehensive learning adventure with our Generative AI and Machine Learning Certificate Program. Delve into the essential concepts of generative AI and machine learning, equipping yourself with the knowledge and skills needed to launch your career in this dynamic field.
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- Comprehensive grasp of procedural and OOP concepts
- Installation of Python and IDE
- Mastery in utilizing Jupyter Notebook
- Implementation of identifiers, indentations, and comments
- Identification of Python data types and operators
- Understanding different types of Python loops
- Exploration of variable scope within functions
- Explanation and understanding of OOP characteristics
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- IBM designed course on Python for data science
- Master Python scripting
- Hands-on data analysis using Jupyter Lab.
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- Introduction to data science and its practical applications
- Grasp the essentials of NumPy
- Investigation into array indexing and slicing techniques
- Application of linear algebra principles in data analysis
- Calculation of central tendency and dispersion measures
- Explanation of null and alternative hypotheses
- Exploration of various hypothesis testing methods including Z-test and T-test
- Understanding the concept of ANOVA (Analysis of Variance)
- Utilization of Pandas for data loading, indexing, reindexing, and merging
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- Investigate the machine learning pipeline and MLOps
- Learn about supervised learning and its applications
- Understand methods to identify and prevent overfitting and underfitting
- Visualize variable linearity using correlation maps
- Explore classification algorithms and their practical usage
- Master various unsupervised learning techniques
- Recognize suitable scenarios for unsupervised algorithms and types of clustering
- Develop a recommendation engine using PyTorch
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- Elevate ML skills with deep learning
- Learn TensorFlow and Keras
- Understand deep learning concepts
- Construct artificial neural networks
- Navigate data abstraction layers
- Unlock data potential for AI advancements
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- Learn about distinctions between deep learning and machine learning
- Understand neural networks, including forward and backward propagation
- Utilize TensorFlow 2 and Keras for model deployment
- Enhance model performance and interpret results effectively
- Explore convolutional neural networks (CNNs) and transfer learning for object detection
- Learn about recurrent neural networks (RNNs) and autoencoders
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- Cutting-edge knowledge: Explore generative AI, prompt engineering, and ChatGPT
- Hands-on skills: Gain practical insights into real-world business applications
- Effective GenAI utilization: Learn to apply Generative AI effectively in various scenarios
- Master prompt engineering: Understand its importance in crafting customized outputs
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- Transformers' significance in modern AI
- Neural networks' suitability for generative tasks
- Differentiate generative model types: VAEs, GANs, transformers, autoencoders
- Appropriate scenarios for diverse generative AI models
- Assess attention mechanisms' efficacy in generative tasks
- Analyze GPT and BERT, contrasting their architectural goals in generative AI
- Langchain and Workflow Design
- Advanced Prompt Engineering Techniques
- LLM Application Development
- LLM Fine-Tuning and Customization
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This will enable you to apply your newly acquired skills. With guidance from mentors, you will build confidence to tackle real-industry challenges. This project not only signifies the peak of your learning journey but also serves as an opportunity to showcase your capabilities to potential employers in a real-world setting.on
Electives:
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- Attain a thorough understanding of computer vision
- Develop expertise in complex neural network architectures
- Learn image creation and manipulation techniques
- Explore CNNs for essential image analysis
- Master object recognition and localization using CNNs
- Apply OCR methods for document digitization
- Gain insights into eXplainable AI (XAI) techniques
- Efficiently deploy deep learning models
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- Explore machine learning algorithms for natural language processing
- Focus on comprehension, feature design, and generation
- Learn automated speech recognition and conversion techniques
- Develop voice assistance tools, including Alexa skills creation
- Emphasize practical application and implementation
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Learn foundational principles of reinforcement learning (RL) Explore various RL approaches using Python and TensorFlow Apply RL techniques and algorithms for problem-solving Gain practical experience in tackling RL challenges
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- Attend an online interactive masterclass delivered by IIT Guwahati faculty
- Gain insights about advancements in technology and techniques in AI and machine learning
- Enhance your knowledge to stay at the forefront of innovation in the constantly evolving landscape of technology
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- Attend online interactive masterclasses delivered by industry leaders from IBM
- Master skills to make data driven decisions, extract business insights, and predict future trends