About Data Science with AI
Develop a strong foundation in data analysis, visualization, and AI-driven approaches to understand complex datasets and support data-driven decisions. Build practical skills for transforming raw data into valuable insights and applying data science concepts to real-world problems.
What you'll Learn
Gain proficiency in supervised and unsupervised machine learning algorithms using Python.
Learn to build and deploy generative models such as GANs and VAEs for image and text generation.
Master the transformer architecture and fine-tune models like GPT for specific tasks.
Explore big data techniques using Apache Spark and create scalable machine learning models.
Course Curriculam
Build a strong foundation in data science, machine learning, and Python programming. Learn how data is collected, prepared, analyzed, and transformed into meaningful insights and predictive solutions.
You’ll explore:
- Introduction to data science and machine learning
- Python fundamentals for data science
- Working with variables, data types, functions, and libraries
- Data collection, preparation, and preprocessing
- Exploratory data analysis and visualization
- Introduction to statistics and probability for data science
- Understanding supervised and unsupervised learning
- Building basic machine learning models with Python
Explore advanced machine learning techniques and understand how data science workflows can scale to large datasets. Learn the fundamentals of deep learning and modern data-driven applications.
You’ll explore:
- Advanced supervised and unsupervised learning techniques
- Feature engineering and model optimization
- Model evaluation and performance improvement
- Introduction to Big Data concepts
- Handling and processing large datasets
- Introduction to neural networks and deep learning
- Deep learning architectures and practical applications
- Applying advanced machine learning workflows
Understand how Generative AI and Large Language Models are transforming data science and intelligent applications. Learn how these technologies can support analysis, automation, content generation, and decision-making.
You’ll explore:
- Introduction to Generative AI and Large Language Models
- Understanding how LLMs process and generate information
- Prompt engineering fundamentals
- Using LLMs for data analysis and interpretation
- AI-assisted coding and data science workflows
- Generating summaries, insights, and reports with AI
- Applications of Generative AI in data science
- Limitations, accuracy, and responsible use of AI
Apply data science, machine learning, and AI concepts using Python to develop practical solutions. Combine programming, data analysis, visualization, and intelligent models to solve real-world problems.
You’ll explore:
- Advanced Python programming for data science
- Working with NumPy, Pandas, and data science libraries
- Advanced data cleaning and transformation
- Data visualization and analytical reporting
- Building and evaluating machine learning models
- Integrating AI and machine learning into Python applications
- Automating data science workflows with Python
- Developing practical AI and data science projects
