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Course Outline
Day 1
- Composition of the Data Science Team (Data Scientist, Data Engineer, Data Visualizer, Process Owner)
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Large Language Models
- Essential libraries for model deployment (Transformers, PyTorch, Ollama)
- Automating the creation of reports using LLMs
- Automatically generating reports with LLMs
-
Business Intelligence
- Categories of Business Intelligence
- Developing Business Intelligence Tools
- The Intersection of Business Intelligence and Data Visualization
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Data Visualization
- The Importance of Data Visualization
- Principles of Visual Data Presentation
- Data Visualization Tools (infographics, dials and gauges, geographic maps, sparklines, heat maps, and detailed bar, pie, and line charts)
- Crafting Visual Stories through Color and Numeracy
- Practical Activity
Day 2
-
Implementing Data Visualization with Python
- Data Science with Python
- Review of Python Fundamentals
- Variables and Data Types (strings, numeric, sequence, mapping, set types, Boolean, binary, casting)
- Operators, Lists, Tuples, Sets, and Dictionaries
- Conditional Statements
- Functions, Lambda, Arrays, Classes, Objects, Inheritance, and Iterators
- Scope, Modules, Date Handling, JSON, RegEx, and PIP
- Exception Handling, Command Input, and String Formatting
- File Handling
- Practical Activity
Day 3
- Integrating Python with MySQL
- Creating Databases and Tables
- Database Manipulation (Insert, Select, Update, Delete, Where Clause, Order By)
- Dropping Tables
- Limiting Results
- Joining Tables
- Removing Duplicates from Lists
- Reversing Strings
-
Data Visualization with Python and MySQL
- Using Matplotlib for Basic Plotting
- Working with Dictionaries and Pandas
- Logic, Control Flow, and Filtering
- Customizing Graph Properties (Font, Size, Color Scheme)
- Practical Activity
Day 4
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Plotting Data in Various Graph Formats
- Histogram
- Line
- Bar
- Box Plot
- Pie Chart
- Donut
- Scatter Plot
- Radar
- Area
- 2D / 3D Density Plot
- Dendrogram
- Map (Bubble, Heat)
- Stacked Chart
- Venn Diagram
- Seaborn
- Practical Activity
Day 5
-
Data Visualization with Python and MySQL
- Group Project: Developing a Data Visualization Presentation for Top Management Using ITDI Local ULIMS Data
- Presentation of Project Outputs
Requirements
- A solid understanding of data structures.
- Prior experience in programming.
Target Audience
- Programmers
- Data Scientists
- Engineers
35 Hours
Testimonials (1)
Trainer was accommodative. And actually quite encouraging for me to take up the course.
