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Course Outline
Day 1
- Composition of Data Science Teams (including Data Scientists, Data Engineers, Data Visualizers, and Process Owners)
-
Large Language Models
- Essential libraries for model deployment (Transformers, PyTorch, Ollama)
- Automating report generation using LLMs
- Automatically producing reports with LLMs
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Business Intelligence
- Different types of Business Intelligence
- Building Business Intelligence Tools
- The intersection of Business Intelligence and Data Visualization
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Data Visualization
- The significance of Data Visualization
- Presenting data visually
- Data Visualization Tools (infographics, dials and gauges, geographic maps, sparklines, heat maps, and detailed bar, pie, and fever charts)
- Crafting Visual Narratives through Numbers and Color
- Activity
Day 2
-
Data Visualization in Python Programming
- 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, Dictionaries
- Conditional Statements
- Functions, Lambda, Arrays, Classes, Objects, Inheritance, Iterators
- Scope, Modules, Dates, JSON, RegEx, PIP
- Try / Except Blocks, Command Input, String Formatting
- File Handling
- Activity
Day 3
- Python and MySQL
- Creating Databases and Tables
- Manipulating Databases (Insert, Select, Update, Delete, Where Clause, Order by)
- Dropping Tables
- Limiting Results
- Joining Tables
- Removing Duplicates from Lists
- Reversing a String
-
Data Visualization with Python and MySQL
- Using Matplotlib (Basic Plotting)
- Dictionaries and Pandas
- Logic, Control Flow, and Filtering
- Modifying Graph Properties (Font, Size, Color Scheme)
- Activity
Day 4
-
Plotting Data in Various Graph Formats
- Histogram
- Line
- Bar
- Box Plot
- Pie Chart
- Donut
- Scatter Plot
- Radar
- Area
- 2D / 3D Density Plot
- Dendrogram
- Maps (Bubble, Heat)
- Stacked Charts
- Venn Diagram
- Seaborn
- Activity
Day 5
-
Data Visualization with Python and MySQL
- Group Work: Create a Top Management Data Visualization Presentation Using ITDI Local ULIMS Data
- Presentation of 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.
