AI (Artificial Intelligence)
- "Empowering tomorrow's possibilities, today, through intelligent artificial intelligence solutions."
(7.5k Learner)
About the course
This course provides a comprehensive introduction to the field of Artificial Intelligence (AI) and explores its various applications in different domains. Students will learn about the foundations of AI, including problem-solving, knowledge representation, and reasoning. They will also gain hands-on experience with popular AI techniques such as machine learning, natural language processing, and computer vision. Through a combination of lectures, practical exercises, and real-world examples, students will develop a strong understanding of AI principles and techniques.
Key Highlights
Innovation Catalyst: AI serves as a catalyst for innovation, driving breakthroughs in technology, business, and society.
Problem Solving: AI enables advanced problem-solving capabilities, tackling complex challenges across diverse domains.
Data Insights: By analyzing vast amounts of data, AI extracts valuable insights to inform decision-making and optimize processes.
Automation: AI automates repetitive tasks, freeing up human resources for more creative and strategic endeavors.
Personalization: AI powers personalized experiences in areas such as e-commerce, healthcare, and entertainment, enhancing customer satisfaction.
Predictive Analytics: AI predicts future trends and behaviors, empowering organizations to anticipate and adapt to changing circumstances.
Enhanced Efficiency: AI streamlines operations, improves efficiency, and reduces costs through intelligent automation and optimization.
Ethical Considerations: As AI advances, it raises important ethical considerations around privacy, bias, and the responsible use of technology.
Human-Machine Collaboration: AI fosters collaboration between humans and machines, augmenting human capabilities and expertise.
Continuous Evolution: AI is constantly evolving, with ongoing research and development pushing the boundaries of what’s possible, ensuring a future of endless possibilities.
What you will learn
Develop a strong understanding of the foundations and principles of AI
Algorithms and Models: Understanding various machine learning algorithms, neural network architectures, and optimization techniques used in AI
Gain hands-on experience with popular AI techniques such as machine learning and deep learning techniques.
Natural Language Processing (NLP): Learning to process and understand human language, including tasks like sentiment analysis, text generation, and language translation.
Explore real-world examples and applications of AI in various domains
Reinforcement Learning: Exploring algorithms for learning optimal decision-making strategies through interaction with an environment.
Ethical and Responsible AI: Understanding ethical considerations, bias detection and mitigation techniques, and ensuring AI systems are developed and deployed responsibly.
Domain-Specific Knowledge: Learning about specific domains such as healthcare, finance, or gaming to provide tailored assistance and insights.
Data Analysis and Interpretation: Acquiring skills in data preprocessing, feature engineering, and statistical analysis to extract meaningful insights from data.
Model Evaluation and Interpretability: Understanding techniques for evaluating model performance and interpreting model predictions to ensure transparency and trustworthiness.
What role does an Advanced Certification in Generative AI & Prompt Engineering play?
Generative AI Engineer
Develop algorithms and create new applications that solve problems and help in easing tasks
Machine Learning Engineer - Generative Models
Specializes in designing machine learning models focused on generative tasks
AI Research Scientist - Generative Modeling
Conduct research on Artificial Intelligence and create new exploring new concepts, algorithms, and methodologies
Data Scientist - Generative Techniques
Responsible for extracting data from different sources using machine learning tools to improve data diversity and robustness.
AI Artist or Creative Technologist
Use generative AI techniques for creating innovative artworks or designs
Creative AI Developer
Responsible for developing effective applications and tools that help in increasing productivity and efficiency
Skills Covered under this Course
Generative AI
Prompt Engineering
ChatGPT
Explainable AI
Generative AI
Architectures
Machine Learning Algorithms
Model Training and Optimization
Natural Language Processing
Curriculum (Module)
- Introduction to Python
- Python Basics (Variables, Comments, Indentation, Input/output, if else, loop statements, break, continue, etc.)
- Data Structures
- Functions
- Object Oriented Programming
- Introduction to commonly used libraries
- Interview Questions
- Hands-on Sessions (Installation of Jupyter Notebook, executing python programs covering the concepts discussed in this module)
- Plotting for exploratory data analysis
- Dimensionality Reduction
- Principal Component Analysis
- T-Sne
- Interview Questions
- Hands-on Sessions (Executing python program covering various dimensionality reduction techniques)
- Introduction to Machine learning
- Regression
- Classification
- Clustering
- Performance Metrics for regression, classification, and clustering
- Interview Questions
- KNN
- Naive Bayes
- Logistic Regression
- Linear Regression
- Support Vector Machine
- Decision Trees
- Ensemble Model
- Feature Engineering for Machine Learning
- Interview Questions
- Hands-on Sessions (Utilising the algorithms discussed in this module with different datasets
- K-Means and K-Means++ Algorithm
- DBSCAN Technique
- Hierarchical Clustering
- Interview Questions
- Hands-on Sessions (Implementation of different clustering algorithms discussed in this module)
- Introduction to Artificial Neural Network
- Backpropagation
- Activation Functions
- Optimizers
- The Vanishing / Exploding Gradients Problems
- Underfitting and Overfitting
- Bias Variance trade-off
- Practical Guidelines to Train Deep Neural Networks
- Interview Questions
- Hands-on Sessions (Implementing MLPs using Keras with TensorFlow Backend and covering the different concepts studied in this module)
- Introduction to CNN
- AlexNet
- VGGNet
- Residual Network
- LeNet
- Inception Network
- ImageNet dataset
- Transfer learning
- Interview Questions
- Hands-on Sessions (Utilizing various algorithms covered in this module with MNIST dataset, Cats/Dogs dataset, ImageNet dataset)
- Introduction to Recurrent Neural Network
- Types of RNNs
- Bidirectional RNN
- Interview Questions
- Hands-on Sessions (IMDB Sentiment classification, Amazon Fine Food reviews)
- Introduction to the platform where the model will be deployed
- Introduction to Front End
- Introduction to Back End
- Building of machine learning and deep learning models and their deployment
- Netflix Movie Recommendation system
To predict whether someone will enjoy a movie based on how much they liked or disliked other movies.
- Taxi Demand Prediction
Given a region and a particular time interval, predict the number of pickups as accurately as possible in that region and nearby regions
- StackoverflowTagPrediction
Suggest the tags based on the content that was there in the question posted on Stack overflow.
- Amazon Fashion Discovery Engine
Build a recommendation engine which suggests similar products to the given product in any e-commerce websites.
- Microsoft Malware Detection
To predict a Windows machine’s probability of getting infected by various families of malware, based on different properties of that machine.
- Predict rating given product reviews on amazon
Predict ratings given Amazon product text reviews
- Quora Question PairSimilarity
So given two questions, our main objective is to find whether they are similar.
Advanced Certification in Generative AI & Prompt Engineering
The Advanced Certification in Generative AI & Prompt Engineering has a lifetime validity. This means that they do not have any expiry date. One can use this certification at any time in their career.
You will receive an Advanced Certification in Generative AI & Prompt Engineering online through the learning management system after completing the course and passing the assignments or exams. Your certificate is available for download and you can share it on LinkedIn.
