Artificial Intelligence – AI
At Divine Tech Skills, we harness the transformative potential of AI-powered development to revolutionize software creation and drive business success. Our AI-driven approach integrates cutting-edge machine learning algorithms and intelligent automation throughout 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 the delivery of high-quality, reliable applications. Our AI-powered tools and platforms offer predictive analytics, facilitating proactive decision-making and rapid problem resolution. With Divine Tech Skills’ AI-powered development, businesses can achieve faster time-to-market, reduced development costs, and innovative products that remain ahead of the competition in a rapidly evolving landscape.
Module 1: AI Overview
Lesson 1: Introduction to AI
- Overview and Evolution of AI
Lesson 2: Types of AI
- Narrow AI vs General AI
- Machine Learning, Deep Learning, and Neural Networks
Lesson 3: AI Applications
- AI Across Industries
- Case Studies and Real-World Examples
Module 2: Configuring the AI Development Environment
Lesson 1: AI Development Tools & Libraries
- Tools: Python, Jupyter Notebooks, Anaconda
- Key Libraries: NumPy, Pandas, Matplotlib, Scikit-learn
Lesson 2: Installing AI Tools
- Setting up the Development Environment
- Cloud-Based AI Platforms: Google Colab, AWS SageMaker
Module 3: AI with Python
Lesson 1: Python Basics
Variables, Data Types, Control Structures, Functions, Modules, and Packages
Lesson 2: Data Manipulation with Pandas
DataFrames, Series, Indexing, Data Cleaning, Transformation, and Visualization
Module 4: Basics of Machine Learning
Lesson 1: Introduction to Machine Learning
- Supervised vs. Unsupervised Learning
- Key Concepts: Training, Testing, and Validation
Lesson 2: Supervised Learning Algorithms
- Linear & Logistic Regression
- Decision Trees, Random Forests, SVM
Lesson 3: Unsupervised Learning Algorithms
- Clustering: K-means, Hierarchical
- Dimensionality Reduction: PCA, LDA
Module 5: Neural Networks
Lesson 1: Introduction to Neural Networks
- Neurons, Layers, Activation, and Loss Functions
Lesson 2: Building Neural Networks with TensorFlow and Keras
- Setting Up and Training Neural Networks
Lesson 3: Convolutional Neural Networks (CNNs)
- CNN Architecture and Image Classification
Lesson 4: Recurrent Neural Networks (RNNs)
- RNN Architecture and Sequence Data Implementation
Module 6: NLP (Natural Language Processing)
Lesson 1: Introduction to NLP
- Key Concepts, Text Preprocessing, Tokenization
Lesson 2: NLP with Python
- Using NLTK, spaCy, Sentiment Analysis, Text Classification
Lesson 3: Advanced NLP Techniques
- Word Embeddings, Word2Vec, Transformers, BERT
Module 7: AI in Manufacturing
Lesson 1: Model Deployment & Monitoring
- Saving and Loading Models
- Deploying with Flask & FastAPI
Lesson 2: Scaling AI Solutions
- Cloud Deployment
- Monitoring & Maintenance
Module 8: Responsible AI and Ethics
Lesson 1: AI Ethics Overview
- Bias and Fairness in AI
- Privacy and Security
Lesson 2: Responsible AI Development
- Ethical AI Best Practices
- Tools and Frameworks for Responsibility
Module 9: Final Project
AI Solution Development: Planning, Model Integration, and Deployment.
Module 10: Final Test
Course Feedback, Exam, Certification & Career Support
- Comprehensive Curriculum: Covers AI fundamentals, machine learning, deep learning, neural networks, and more.
- Industry-Relevant Skills: Equip learners with in-demand AI skills used across industries.
- Practical Hands-on Learning: Real-world projects and case studies for applied AI experience.
- Expert Instructors: Learn from AI professionals with years of industry expertise.
- Career Support: Personalized career guidance, job placement assistance, and interview prep.
- Flexible Learning: Accessible online with flexible schedules to suit working professionals.
