Artificial Intelligence
Artificial Intelligence Training In Bhubaneswar
Dive into the future of technology with Artificial Intelligence (AI) training at Logic Wave in Bhubaneswar. As AI continues to revolutionize industries, our training program is designed to equip you with the cutting-edge skills needed to excel in this rapidly evolving field.
At Logic Wave, you will learn from experienced instructors who provide hands-on, practical knowledge in AI. Our comprehensive curriculum covers essential topics such as machine learning, neural networks, natural language processing, and computer vision. You will work on real-world projects and case studies to gain practical experience and understand how AI can be applied to solve complex problems.
Our training emphasizes a practical approach, ensuring you can develop, deploy, and manage AI solutions effectively. We also provide guidance on industry trends and career development to help you stay ahead in the AI landscape.
Logic Wave offers a modern, supportive learning environment that fosters growth and innovation. Join us to enhance your expertise in artificial intelligence and open doors to exciting career opportunities in this transformative field.
Course Duration
3 Months
Course Fees
₹ 15,000
Includes
Artificial Intelligence, NLP, ML, AI Deployment
Course Days
Weekly 3 Days
Course Overview and Modules
- Overview of Artificial Intelligence (AI) and its significance
- History and evolution of AI
- Key concepts and types of AI (Narrow AI, General AI, Superintelligent AI)
- Applications of AI across various industries
- Setting up the Python environment for AI development
- Essential Python libraries for AI (NumPy, pandas, SciPy)
- Working with data using Python
- Introduction to machine learning concepts
- Supervised vs. unsupervised learning
- Key algorithms (linear regression, k-nearest neighbors, clustering)
- Model evaluation metrics (accuracy, precision, recall, F1 score)
- Understanding neural networks and their components
- Introduction to deep learning frameworks (TensorFlow, Keras, PyTorch)
- Building and training basic neural networks
- Understanding activation functions and loss functions
- Convolutional Neural Networks (CNNs) for image processing
- Recurrent Neural Networks (RNNs) and Long Short-Term Memory (LSTM) networks for sequential data
- Generative Adversarial Networks (GANs) and their applications
- Transfer learning and pre-trained models
- Basics of NLP and its applications
- Text preprocessing techniques (tokenization, stemming, lemmatization)
- Building and training language models (word embeddings, transformers)
- Sentiment analysis, named entity recognition, and text generation
- Introduction to reinforcement learning concepts
- Key components: agents, environments, rewards
- Exploration vs. exploitation dilemma
- Implementing algorithms (Q-learning, policy gradients)
- Image processing techniques and algorithms
- Object detection and recognition
- Image segmentation and classification
- Applications of computer vision (face recognition, autonomous vehicles)
- Basics of robotics and AI integration
- Robot perception and control systems
- Path planning and autonomous navigation
- Applications of AI in robotics (manufacturing, healthcare)
- Understanding ethical considerations in AI
- Addressing biases and fairness in AI systems
- Ensuring transparency and accountability
- Privacy and data protection issues
- Model deployment strategies (cloud services, on-premises)
- Building scalable AI applications
- Monitoring and maintaining AI systems
- Handling production challenges and performance tuning
- Overview of AI development tools and platforms (Google AI, Microsoft Azure AI, AWS AI)
- Using pre-built AI services and APIs
- Integration with existing systems and workflows
- Developing end-to-end AI projects from concept to deployment
- Project planning and management
- Case studies of successful AI implementations
- Best practices for project development
- Emerging trends and advancements in AI
- The impact of AI on various sectors (healthcare, finance, education)
- Preparing for future developments and technologies