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Course Outline
Day 1
- Structure of a Data Science Team (Data Scientist, Data Engineer, Data Visualizer, Process Owner)
-
Large Language Models
- Essential libraries for model deployment (Transformers, PyTorch, Ollama)
- Automating report generation using LLMs
- Streamlining report creation with LLMs
-
Business Intelligence
- Categories of Business Intelligence
- Building Business Intelligence Tools
- The intersection of Business Intelligence and Data Visualization
-
Data Visualization
- The significance of Data Visualization
- Techniques for Visual Data Presentation
- Data Visualization Tools (infographics, dials and gauges, geographic maps, sparklines, heat maps, and detailed bar, pie and fever charts)
- Crafting Visual Narratives through Color and Numbers
- Practical Exercise
Day 2
-
Data Visualization in Python
- Data Science applications with Python
- Review of Python Fundamentals
- Variables and Data Types (str, 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, Command Input, String Formatting
- File Handling
- Practical Exercise
Day 3
- Python and MySQL
- Creating Database and Table
- Manipulating Database (Insert, Select, Update, Delete, Where Statement, Order by)
- Drop Table
- Limit
- Joining Tables
- Removing List Duplicates
- Reverse a String
-
Data Visualization with Python and MySQL
- Using Matplotlib (Basic Plotting)
- Dictionaries and Pandas
- Logic, Control Flow and Filtering
- Manipulating Graphs Properties (Font, Size, Color Scheme)
- Practical Exercise
Day 4
-
Plotting Data in Different Graph Format
- Histogram
- Line
- Bar
- Box Plot
- Pie Chart
- Donut
- Scatter Plot
- Radar
- Area
- 2D / 3D Density Plot
- Dendogram
- Map (Bubble, Heat)
- Stacked Chart
- Venn Diagram
- Seaborn
- Practical Exercise
Day 5
-
Data Visualization with Python and MySQL
- Group Work: Create a Top Management Data Visualization Presentation Using ITDI Local ULIMS Data
- Presentation of Output
Requirements
- Foundational knowledge of Data Structures.
- Prior experience in Programming.
Target Audience
- Software Programmers
- Data Scientists
- Engineers
35 Hours
Testimonials (1)
Trainer was accommodative. And actually quite encouraging for me to take up the course.
