Welcome to Data Science with Generative AI Course , we will cover Machine Learning , Deep Learning , Generative AI courses
Curriculum
- 11 Sections
- 112 Lessons
- 16 Weeks
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- Introduction to Python10
- Pandas12
- 2.1Data Frame – Series of Data
- 2.2Installing and importing Pandas
- 2.3Creating and Inspecting Data
- 2.4Creating DataFrames from Dictionary from other sources
- 2.5Indexing and Selection
- 2.6Data Cleaning and Preprocessing
- 2.7Data Transformation
- 2.8Handling Categorical Data
- 2.9Grouping and Aggregation
- 2.10Reshaping and Pivoting
- 2.11Working with Dates and Times
- 2.12Combining Datasets
- Numpy10
- MatPlotLib10
- 4.1Introduction to Matplotlib
- 4.2Basic Plotting with Pyplot
- 4.3Understanding Figure and Axes
- 4.4Common Plot Types for Data Science
- 4.5Customizing Plots
- 4.6Working with Subplots
- 4.7Styling and Themes
- 4.8Plotting with Pandas + Matplotlib
- 4.9Handling Categorical and Time-Series Data
- 4.10Saving and Exporting Figures
- Seaborn10
- 5.1Introduction to Seaborn
- 5.2Seaborn vs. Matplotlib: When to Use Which
- 5.3Built-in Datasets and Plot Styling
- 5.4Categorical Plots (Comparing groups)
- 5.5Relational Plots (Relationships between variables)
- 5.6Distribution Plots (Univariate & Bivariate)
- 5.7Regression and Correlation Visualization
- 5.8Matrix and Grid Plots
- 5.9Multi-Plot Figures with Figure-Level Functions
- 5.10Customization and Integration
- Scikit-Learn10
- 6.1Introduction to scikit-learn
- 6.2Data Representation in scikit-learn
- 6.3Train-Test Splitting and Cross-Validation
- 6.4Preprocessing and Feature Engineering
- 6.5Supervised Learning – Regression
- 6.6Supervised Learning – Classification
- 6.7Model Selection and Hyperparameter Tuning
- 6.8Unsupervised Learning
- 6.9Model Evaluation Deep Dive
- 6.10Pipelines and Production Readiness
- Machine Learning10
- 7.1Introduction to Machine Learning
- 7.2The Machine Learning Project Lifecycle
- 7.3Data Preprocessing & Feature Engineering
- 7.4Model Evaluation & Validation
- 7.5Supervised Learning Algorithms
- 7.6Unsupervised Learning
- 7.7Model Selection & Hyperparameter Tuning
- 7.8Introduction to Model Interpretability
- 7.9Handling Imbalanced Data (Classification)
- 7.10Introduction to Ethical ML & Responsible AI
- Deep Learning10
- 8.1Introduction to Deep Learning
- 8.2Neural Network Fundamentals
- 8.3Building & Training Models with TensorFlow/Keras
- 8.4Data Preprocessing for Deep Learning
- 8.5Model Evaluation & Diagnostics
- 8.6Convolutional Neural Networks (CNNs) – For Image Data
- 8.7Recurrent Neural Networks (RNNs) – For Sequential Data
- 8.8Embeddings & Introduction to NLP with DL
- 8.9Introduction to Transformers & Modern Architectures (Conceptual)
- 8.10Generative Deep Learning (Overview & Projects)
- Generative AI10
- 9.1Introduction to Generative AI
- 9.2Foundations: Probability, Latent Space & Representation Learning
- 9.3Autoencoders (AEs) and Variational Autoencoders (VAEs)
- 9.4Generative Adversarial Networks (GANs)
- 9.5Sequence Generation with RNNs and LSTMs
- 9.6Transformers and Large Language Models (LLMs)
- 9.7Foundation Models & Retrieval-Augmented Generation (RAG)
- 9.8Diffusion Models (Modern Image/Video Generation)
- 9.9Evaluation of Generative Models
- 9.10Ethical, Societal, and Safety Considerations
- Fundamentals of Data Science & AIExplore core concepts in data science and the basics of AI models like machine learning and deep learning.12
- 10.1Introduction to Data Science
- 10.2What is Artificial Intelligence?
- 10.3Introduction to Machine Learning
- 10.4Supervised vs. Unsupervised Learning
- 10.5Data Collection and Preparation
- 10.6Feature Engineering Basics
- 10.7Understanding Deep Learning
- 10.8Training and Evaluating Models
- 10.9Use Cases of ML and DL
- 10.10Ethics in Data Science and AI
- 10.11Foundations of Data Science Quiz0 Questions
- 10.12AI and ML Concepts Quiz0 Questions
- Generative AI and Next-Gen ApplicationsDive into generative AI, including models like ChatGPT, and learn real-world applications and future trends in AI.12
- 11.1What is Generative AI?
- 11.2Exploring Language Models
- 11.3Generative AI for Images and Art
- 11.4Hands-On with AI Text Generation
- 11.5Introduction to GANs
- 11.6Safe Use of Generative AI Tools
- 11.7Applications in Business and Science
- 11.8Future of Generative Technologies
- 11.9Common Challenges and Limitations
- 11.10Careers in AI and Data Science
- 11.11Generative AI Concepts Quiz0 Questions
- 11.12Responsible AI and Applications Quiz0 Questions
Instructor
