https://github.com/codewitheshayoutube/corvit_python_data_analytics_course
I teach Python & Data Analytics at Corvit Systems. This repository contains all course materials, including code, assignments, projects, and resources. ⭐ Stay updated!
https://github.com/codewitheshayoutube/corvit_python_data_analytics_course
matplotlib numpy pandas python python3 scikitlearn-machine-learning seaborn
Last synced: 2 months ago
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I teach Python & Data Analytics at Corvit Systems. This repository contains all course materials, including code, assignments, projects, and resources. ⭐ Stay updated!
- Host: GitHub
- URL: https://github.com/codewitheshayoutube/corvit_python_data_analytics_course
- Owner: codewithEshaYoutube
- Created: 2025-02-18T16:34:37.000Z (11 months ago)
- Default Branch: main
- Last Pushed: 2025-02-18T16:47:58.000Z (11 months ago)
- Last Synced: 2025-02-18T17:41:13.257Z (11 months ago)
- Topics: matplotlib, numpy, pandas, python, python3, scikitlearn-machine-learning, seaborn
- Homepage:
- Size: 3.91 KB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Corvit Python Data Analytics Course
## 📢 Important Notice
> ⭐ **Connect with me on GitHub and LinkedIn!** All course training code and important updates will be uploaded here. Don't forget to star the repository!
>
> 📌 **Instructor:** [Eesha Tariq](https://www.linkedin.com/in/esha-tariqdev/)
>
> 🌐 **Institution:** [Corvit Systems](https://corvit.com/systems/) (Onsite Training in Pakistan)
---
## 📚 Course Overview
This **3-month Python & Data Analytics course** at Corvit Systems is designed to equip students with essential programming and data analysis skills. The course covers:
- **Python Programming Basics**: Syntax, Data Types, Loops, Functions
- **Data Analytics**: NumPy, Pandas, Data Wrangling & Visualization
- **Machine Learning Fundamentals**: Scikit-learn, Model Evaluation
- **Database Management**: SQL and NoSQL databases
- **Real-world Projects**: Hands-on practical experience by building data-driven applications
## 🗂 Repository Structure
- **Week-wise Modules**: Structured notebooks for each topic
- **Assignments**: Hands-on coding exercises
- **Projects**: Real-world applications using Python & Data Analytics
- **Resources**: Additional reading material and references
- **Final Test & Certification**: Onsite evaluation for certification
## 🏆 Weekly Course Structure
### 📌 Week 1: Python Fundamentals
- Introduction to Python
- Variables, Data Types, Operators
- Control Flow (Loops & Conditionals)
- Functions and Modules
### 📌 Week 2: Data Structures & File Handling
- Lists, Tuples, Sets, Dictionaries
- File Handling (Reading/Writing Files)
- Exception Handling
### 📌 Week 3: Object-Oriented Programming (OOP)
- Classes and Objects
- Encapsulation, Inheritance, Polymorphism
### 📌 Week 4: Introduction to NumPy & Pandas
- NumPy Arrays and Operations
- Pandas DataFrames: Data Manipulation & Cleaning
### 📌 Week 5: Data Visualization
- Matplotlib & Seaborn for Charts and Graphs
- Interactive Visualizations
### 📌 Week 6: SQL for Data Analysis
- SQL Basics: Queries, Joins, Aggregations
- Connecting Python with SQL Databases
### 📌 Week 7: Machine Learning Fundamentals
- Supervised vs Unsupervised Learning
- Building ML Models using Scikit-learn
### 📌 Week 8-11: Real-World Data Analytics Projects
- **Project 1**: Exploratory Data Analysis (EDA)
- **Project 2**: Data Cleaning & Visualization
- **Project 3**: Predictive Analytics using ML
### 📌 Week 12: Capstone Project & Career Guidance
- Final project presentation
- Resume building & interview preparation
- **Final Test for Certification**
## 🚀 Why Take This Course?
- **Industry-relevant curriculum** taught by expert instructor **[Eesha Tariq](https://www.linkedin.com/in/esha-tariqdev/)**
- **Hands-on learning** with real-world **projects**
- **Access to GitHub repository** for course material and assignments
- **Career growth opportunities** in Data Science & AI
## 📖 Student Guide
To ensure a smooth learning experience, follow these guidelines:
1. **Pre-requisites**:
- Basic understanding of programming concepts is helpful but not required.
- Install Python, Jupyter Notebook, and necessary libraries before the course starts.
2. **Course Structure**:
- Each module includes lectures, coding exercises, and real-world projects.
- Weekly assignments to reinforce learning.
- A final capstone project to showcase your skills.
- **Final Test will be conducted onsite for certification.**
3. **Resources**:
- Course materials and notebooks available on the GitHub repository.
- Recommended books and online references will be shared.
- Additional support for students via discussion forums.
4. **Support & Queries**:
- Join the dedicated student discussion group.
- Reach out to the instructor for guidance via LinkedIn or email.
## 📌 How to Enroll?
Visit [Corvit Systems](https://corvit.com/systems/) for enrollment details or contact **Eesha Tariq** via LinkedIn.
## 🔗 Connect with Me
[](mailto:tariqeesha321@gmail.com)
[](https://www.linkedin.com/in/esha-tariqdev/)
[](https://github.com/codewithEshaYoutube)
---
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