Artificial Intelligence - AI
Artificial Intelligence - AI
Price ₹20,999 + Gst
At ScalarUpskill, we harness the transformative potential of AI-powered development to revolutionize software creation and enhance business outcomes. Our AI-driven approach integrates advanced machine learning algorithms and intelligent automation into the development lifecycle, enabling us to deliver smarter, faster, and more efficient solutions. By leveraging AI, we optimize coding practices, automate repetitive tasks, and enhance software testing, ensuring high-quality, reliable applications. Our AI-powered tools and platforms provide predictive analytics, enabling proactive decision-making and rapid problem resolution. With ScalarUpskill’s AI-powered development, businesses can achieve accelerated time-to-market, reduced development costs, and innovative products that stay ahead of the curve in an increasingly competitive landscape.
Artificial Intelligence - AI Course Curriculum
Lesson 1: What is AI?
- Overview of Artificial Intelligence
- History and Evolution of AI
Lesson 2: Types of AI
- Narrow AI vs General AI
- Machine Learning, Deep Learning, and Neural Networks
Lesson 3: Applications of AI
- AI in Various Industries
- Case Studies and Real-World Applications
Lesson 1: Tools and Libraries for AI Development
- Python, Jupyter Notebooks, Anaconda
- Key Libraries: NumPy, Pandas, Matplotlib, Scikit-learn
Lesson 2: Installing and Configuring AI Tools
- Setting Up the Development Environment
- Introduction to Cloud-Based AI Platforms (e.g., Google Colab, AWS SageMaker)
Lesson 1: Python Basics
- Variables, Data Types, and Control Structures
- Functions, Modules, and Packages
Lesson 2: Data Manipulation with Pandas
- DataFrames, Series, and Indexing
- Data Cleaning, Transformation, and Visualization
Lesson 1: Introduction to Machine Learning
- Supervised vs Unsupervised Learning
- Key Concepts: Training, Testing, and Validation
Lesson 2: Supervised Learning Algorithms
- Linear Regression, Logistic Regression
- Decision Trees, Random Forests, Support Vector Machines
Lesson 3: Unsupervised Learning Algorithms
- Clustering: K-means, Hierarchical Clustering
- Dimensionality Reduction: PCA, LDA
Lesson 1: Introduction to Neural Networks
- Understanding Neurones and Layers
- Activation Functions and Loss Functions
Lesson 2: Building Neural Networks with TensorFlow and Keras
- Setting Up TensorFlow and Keras
- Creating, Training, and Evaluating Neural Networks
Lesson 3: Convolutional Neural Networks (CNNs)
- CNN Architecture and Applications
- Implementing CNNs for Image Classification
Lesson 4: Recurrent Neural Networks (RNNs)
- RNN Architecture and Applications
- Implementing RNNs for Sequence Data
Lesson 1: Introduction to NLP
- Key Concepts and Techniques
- Text Preprocessing and Tokenization
Lesson 2: NLP with Python
- Using NLTK and spaCy
- Sentiment Analysis and Text Classification
Lesson 3: Advanced NLP Techniques
- Word Embeddings and Word2Vec
- Transformers and BERT
Lesson 1: Model Deployment and Monitoring
- Saving and Loading Models
- Deploying AI Models with Flask and FastAPI
Lesson 2: Scaling AI Solutions
- Using Cloud Platforms for Deployment
- Monitoring and Maintaining AI Models
Lesson 1: Understanding AI Ethics
- Bias and Fairness in AI
- Privacy and Security Considerations
Lesson 2: Responsible AI Development
- Best Practices for Ethical AI
- Tools and Frameworks for Responsible AI
Project Planning and Implementation
- Developing an End-to-End AI Solution
- Integrating Machine Learning and Deep Learning Models
- Deploying the AI Solution to Production
Course Review and Q&A
- Final Examination
- Certification and Career Guidance
