| Course Name | Duration | Classes | Total Fee | Mode of Training | Class Timing |
|---|---|---|---|---|---|
|
Pandas Analysis
Course |
2 Months |
40 |
60,000 PKR |
Online & Face-to-Face |
To be decided mutually with students |
Pandas Analysis Training Certification Course
Technocation provides an excellent faculty and qualified developers as there is a remarkable prospect in this field. One can make his/her Career with the help of both Pandas Training and establish an identity and get guidance in Rawalpindi.
Therefore, we aim to shape inspiring students with in-depth training to meet the requirements of the IT industry and build substantial grounds in Pandas Analysis Training by exhibiting students with various projects. Technocation also bestows the Best Analysis Training Course in Rawalpindi, Islamabad.
We guide people from every background to change their lives via our career-oriented short-term courses in Rawalpindi. Our evening and online course primarily focus on school, college, university students, and full/part-time employees.
Advantages of Learning Pandas Analysis
- Simplifies data manipulation and cleaning.
- Handles diverse data sources (CSV, Excel, SQL).
- Efficiently processes large datasets.
- Supports time-series analysis.
- Integrates with Python libraries (NumPy, Matplotlib).
- Enables quick data exploration and summarization.
- Facilitates automation of repetitive tasks.
- Provides high performance and flexibility.
- Essential skill for data science and analysis.
- Backed by strong community and documentation.
Pandas Analysis Training Certification Course Outline
A comprehensive Pandas-Analysis Advanced Level Course outline focuses on deep, hands-on learning with advanced concepts in data manipulation, analysis, and visualization using Pandas. Below is a suggested outline:
Module 1:Advanced Data Structures
- MultiIndex and Advanced Indexing
- Hierarchical Indexing
- Custom Indexing Techniques
Module 2:Advanced Data Cleaning
- Handling Missing Data (imputation techniques, dropna)
- Data Transformation (scaling, encoding)
- Data Deduplication and Filtering
Module 3:Data Manipulation Techniques
- Complex Merging and Joining (left, right, outer, inner joins)
- Concatenation and Stacking/Unstacking
- Efficient GroupBy Operations (aggregation, pivoting)
Module 4:Data Aggregation and Group Operations
- Pivot Tables and Cross Tables
- Advanced GroupBy Operations with custom aggregation
- Grouping with multiple aggregations and nested operations
Module 5:Performance Optimization
- Memory Management and Data Type Optimization
- Parallel Processing with Pandas (dask integration)
- Optimized Operations with NumPy Integration
Module 6:Advanced Data Visualization
- Creating Custom Visualizations (heatmaps, radar plots, etc.)
- Interactive Visualizations with Plotly, Bokeh, or Seaborn
- Advanced Data Storytelling with Visualizations
Module 7:Working with Time Series Data
- Advanced Time Series Operations (resampling, rolling, shifting)
- Handling Date Ranges and Time Zones
- Forecasting and Seasonal Decomposition
Module 8:Data Validation and Transformation
- Regular Expressions and Data Cleaning
- Applying Complex Functions to Columns and Series
- Vectorized Operations for Performance Improvement
Module 9: Data Export and Integration
- Exporting Data to SQL, Excel, and Other Formats
- Integrating Pandas with Web APIs
- Database Interaction using Pandas
Experience and Inspiring Trainers:
Real-time Practice and Projects:
Understanding of variables, data types, loops, functions, and file handling.
Prerequisites for Pandas Analysis Course:
- Familiarity with Data Structures: Lists, dictionaries, and tuples in Python.
- Basic Math Skills: Fundamental arithmetic and statistics concepts.
- Intro to Libraries: Experience with installing and importing Python libraries.
- Jupyter Notebooks (Optional): Familiarity with using Jupyter Notebook for coding.
Certificate:
Course Material:
Support and Careers Advice:
“Our Student Success is Our Mission”.