Skillfloor offers a robust Artificial Intelligence and Machine Learning Program in Aurangabad, catering to both beginners and professionals aiming to excel in the AI field. This course covers essential topics like machine learning, data science, and data analytics, providing students with the expertise to address real-world challenges effectively. Through a balance of theoretical knowledge and hands-on projects, learners gain a comprehensive understanding of AI algorithms, models, and tools that are transforming modern industries.
The AI curriculum at Skillfloor emphasizes practical learning, engaging students with real-life projects and case studies crafted by industry experts. This ensures students remain up-to-date with evolving trends in AI and data analytics. Recognized as a top AI training institute in Aurangabad, Skillfloor also provides internship opportunities, allowing learners to gain industry experience and build essential skills in a professional setting. This practical approach equips graduates with the confidence and competence to thrive in AI careers in today’s competitive job market.
₹60,000
The Artificial Intelligence Certification in Aurangabad equips you with essential AI skills and practical knowledge for real-world applications. Covering fundamental topics like machine learning, data science, and AI tools, this program offers hands-on experience through projects and case studies. Whether you’re new to AI or aiming to advance your career, the certification provides a strong foundation for working with AI technologies. By completing this course, you’ll gain the expertise to apply AI across different industries, enhancing your professional value in the rapidly expanding field of artificial intelligence.
- Overview of AI and ML
- Types of Machine Learning
- Data Collection and Preprocessing
- Basic Statistics for AI
- Python Essentials for AI
- Regression Analysis
- Classification Algorithms
- Ensemble Methods
- Model Evaluation Techniques
- Feature Engineering and Selection
- Introduction to Clustering
- Dimensionality Reduction Techniques
- Association Rule Learning
- Anomaly Detection
- Self-Organizing Maps (SOM)
- Introduction to Neural Networks
- Deep Neural Networks (DNNs)
- Convolutional Neural Networks (CNNs)
- Recurrent Neural Networks (RNNs)
- Autoencoders and Generative Models
- Introduction to NLP and Text Processing
- Text Classification and Sentiment Analysis
- Advanced NLP Techniques
- Deep Learning in NLP
- Speech Recognition and Processing
- Introduction to Computer Vision
- Image Classification with CNNs
- Object Detection Techniques
- Image Segmentation
- Video Processing and Analysis
- Introduction to Reinforcement Learning
- Markov Decision Processes (MDP)
- Q-Learning and SARSA
- Deep Q Networks (DQN)
- Applications of Reinforcement Learning
- Ethical Implications of AI
- Fairness and Bias in AI
- Privacy and Security Concerns
- Explainability in AI
- Legal and Regulatory Aspects
- AI in Healthcare
- AI in Finance
- AI in Manufacturing
- AI in Retail
- AI in Autonomous Systems
- Defining and Planning a Capstone Project
- Data Preparation for Projects
- Model Building and Testing
- Model Deployment Techniques
- Project Presentation and Evaluation