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Curriculum Designed By Experts
Expertly designed curriculum for future-ready professionals.
Industry Oriented Curriculum
An exhaustive curriculum designed by our industry experts which will help you to get placed in your dream IT company
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30+ Case Studies & Projects
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9+ Engaging Projects
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10+ Years Of Experience
GenAI and ML Training Projects
Become a GenAI and ML Expert With Practical and Engaging Projects.
- Practice essential Tools
- Designed by Industry experts
- Get Real-world Experience
Text Generation Chatbot
Create a simple chatbot using pre-trained language models to respond to user queries, focusing on prompt design and basic API integration.
Image Style Transfer
Implement an application that applies artistic styles to images using pre-built neural networks, exploring basic computer vision concepts.
AI-Powered Text Summarizer
Develop a tool that condenses long texts into concise summaries using NLP models, emphasizing text preprocessing and model inference.
Custom Fine-Tuned Language Model
Fine-tune a transformer-based model on a specific dataset to generate domain-specific text outputs, learning model training and evaluation.
GAN-based Image Generation
Build a Generative Adversarial Network to create realistic images, understanding GAN architecture and training stability techniques.
AI-driven Content Moderation System
Create a system that automatically detects and flags inappropriate content using text and image analysis, focusing on multi-modal AI.
Multimodal AI Assistant
Develop an assistant capable of understanding and generating text, images, and voice commands, integrating multiple generative models.
Deepfake Video Generation
Build a system to create realistic synthetic videos, learning advanced GANs and ethical considerations in synthetic media.
AI-Based Code Generation Platform
Create an intelligent coding assistant that generates, debugs, and explains code snippets using large language models fine-tuned for programming tasks.
Key Features
Practical Training
Global Certifications
Flexible Timing
Trainer Support
Study Material
Placement Support
Mock Interviews
Resume Building
Batch Schedule
Weekdays Regular (Class 1Hr - 1:30Hrs) / Per Session
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13 - Oct - 2025 Starts Coming Monday ( Monday - Friday) 08:00 AM (IST)
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15 - Oct - 2025 Starts Coming Wednesday ( Monday - Friday) 10:00 AM (IST)
Weekend Regular (Class 3Hrs) / Per Session
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18 - Oct - 2025 Starts Coming Saturday ( Saturday - Sunday) 10:00 AM (IST)
Weekend Fast-track (Class 6Hrs - 7Hrs) / Per Session
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19 - Oct - 2025 Starts Coming Saturday ( Saturday - Sunday) 10:00 AM (IST)
Enquiry Form
- Learning strategies that are appropriate and tailored to your company's requirements.
- Live projects guided by instructors are a characteristic of the virtual learning environment.
- The curriculum includes of full-day lectures, practical exercises, and case studies.
GenAI courseOverview
Reasons to Consider Enrolling in Generative AI and Machine Learning Placement Programs Online
Enrolling in Generative AI And Machine Learning Training offers flexible learning tailored to current industry demands. These programs provide hands-on experience with real-world datasets and projects, enhancing practical skills. Learners benefit from expert mentorship, interview preparation, and access to job placement assistance. Additionally, the convenience of learning remotely allows balancing education with personal and professional commitments. The evolving AI landscape makes these skills highly sought-after, offering promising career opportunities. Online platforms also offer a diverse community for networking and collaboration.
Overview of the Most Recent GenAI and ML Certification in Online Tools
Modern training tools in GenAI and Machine Learning Course in Online emphasize ease of use, scalability, and integration with cloud platforms. Frameworks like TensorFlow, PyTorch, and Hugging Face simplify building and deploying models with extensive prebuilt components. Cloud services from AWS, Google Cloud, and Azure provide powerful GPUs and pre-configured environments for training large models. Tools such as Jupyter Notebooks and Google Colab support interactive experimentation and visualization. AutoML platforms enable automated model tuning, reducing manual effort. Collaborative tools like Weights & Biases facilitate tracking and managing experiments seamlessly.
Techniques and Trends Observed in GenAI and ML Training Course
- Hands-On Project-Based Learning: Most courses emphasize real-world projects, enabling learners to apply theoretical knowledge in practical scenarios and build portfolios.
- Use of Pretrained Models and Transfer Learning: Training programs increasingly incorporate pretrained models, allowing faster learning and better results with limited data.
- Integration of Cloud Computing Resources: Cloud platforms are heavily used to provide scalable computational power and access to state-of-the-art hardware without large investments.
- Focus on Explainability and Ethics: Courses are paying more attention to responsible AI, teaching techniques for model transparency, fairness, and ethical considerations.
- Hybrid Learning Models: Blending self-paced learning with live sessions and mentorship helps improve engagement and personalized support.
Requirements Needed for a GenAI and ML Placement in Online
- Basic Programming Knowledge: Familiarity with languages like Python is essential since most AI frameworks and libraries use Python.
- Understanding of Mathematics: A grasp of linear algebra, calculus, probability, and statistics is crucial to comprehend machine learning algorithms deeply.
- Access to a Computer with Good Processing Power: While many cloud options exist, having a capable local machine helps with faster development and testing.
- Willingness to Learn and Experiment: Success requires consistent practice, curiosity, and a problem-solving mindset to navigate complex AI challenges.
- Familiarity with Data Handling: Basic knowledge of data preprocessing, cleaning, and manipulation is needed to prepare datasets for training models.
Goals Achieved Through GenAI and ML Certification in Online and Potential Career Paths
Completing GenAI and Machine Learning Course in Online equips learners with the ability to design, develop, and deploy AI-driven solutions across diverse domains. Graduates gain proficiency in deep learning architectures, data modeling, and AI ethics, enabling them to contribute effectively to innovation-driven projects. The skills acquired open doors to careers such as AI Engineer, Machine Learning Specialist, Data Scientist, Research Scientist, and AI Product Manager. Additionally, professionals can work in industries like healthcare, finance, entertainment, and autonomous systems, where AI adoption is accelerating rapidly.
Career Opportunities After GenAI Training
AI Research Scientist
Designs and experiments with novel AI models and algorithms, pushing the boundaries of generative AI technologies.
Machine Learning Engineer
Builds, tests, and deploys machine learning models into production environments, ensuring scalability and efficiency for real-world applications.
Data Scientist
Analyzes large datasets to extract meaningful insights and develops predictive models using generative AI techniques to solve business problems.
Deep Learning Engineer
Specializes in neural networks and deep learning architectures, optimizing generative models such as GANs and VAEs for tasks like image and text generation.
AI Product Manager
Leads AI-driven product development, translating technical AI capabilities into market-ready products that solve user needs and enhance user experience.
AI Ethics Specialist
Focuses on ethical AI use, ensuring generative models comply with fairness, transparency, and privacy standards, and mitigating biases in AI systems.
Skill to Master
Neural Network Architecture
Scrum framework and roles
Generative Adversarial Networks
Natural Language Processing
Computer Vision
Reinforcement Learning
Data Preprocessing and Augmentation
Model Evaluation and Validation
TensorFlow and PyTorch Frameworks
Transfer Learning
AI Ethics and Fairness
Cloud AI Services
Tools to Master
TensorFlow
PyTorch
Hugging Face Transformers
OpenAI GPT APIs
Google Colab
Jupyter Notebook
Keras
Scikit-learn
Docker
Weights & Biases
MLflow
NVIDIA CUDA Toolkit
Learn from certified professionals who are currently working.
Training by
Ravi, having 11 yrs of experience
Specialized in: GenAI training focusing on transformer-based language models, computer vision applications, and ethical AI deployment.
Note: Ravi is recognized for her deep knowledge of container orchestration and his ability to bridge the gap between development and operations teams.
We are proud to have participated in more than 40,000 career transfers globally.
GenAI and ML Certification
Yes, GenAI and ML Certification Course guarantee a job. Success depends on your ability to demonstrate skills through projects, interviews, and continuous learning in a competitive market.
Most exams require foundational knowledge of programming (Python preferred), understanding of basic machine learning concepts, and completion of the core training modules. Some institutes may recommend prior experience but it varies.
Yes, many institutes now offer proctored online exams allowing you to complete certifications remotely. This enables flexibility without compromising exam integrity.
Yes, Given the explosive growth and diverse applications of AI, investing in quality training offers high returns in job opportunities, innovation potential, and career growth in multiple industries.
Frequently Asked Questions
- Most Generative AI and Machine Learning courses provide flexible learning modes, including both online and classroom options, catering to different learning preferences and schedules.
- The GenAI and ML Training Course typically lasts between 3 to 6 months.
- The duration may vary based on the course intensity and whether it’s part-time or full-time.
- Placement support usually includes resume building, mock interviews, and job referrals through partnerships with tech companies
- GenAI and ML Placement Course offering direct placement assistance upon successful course completion
- Yes, most programs incorporate hands-on projects based on real-world AI problems, helping you gain practical experience and build a professional portfolio.
- Interview preparation, including coding challenges, technical question practice, and soft skills training, is commonly included to boost confidence and readiness for job interviews.