Learning Management System (LMS)

Overview

This project aims to build an innovative and engaging Learning Management System (LMS) using Data Science and Machine Learning techniques. The LMS focuses on providing students with a non-boring and interactive learning experience. By integrating advanced machine learning algorithms, the platform ensures personalized and effective learning paths.

Features

Interactive Learning Modules: Engaging content tailored to students' needs.
Personalized Recommendations: AI-powered suggestions for courses and materials.
Progress Tracking: Monitor student performance and provide insights.
Data-Driven Insights: Leverage analytics to improve learning outcomes.
Scalable Design: Built for growth and seamless integration with new technologies.

Technologies Used

Programming Languages: Python, JavaScript
Frameworks: Flask/Django, React
Machine Learning Libraries: TensorFlow, Scikit-learn
Database: PostgreSQL/MySQL
Deployment: Docker, AWS/GCP

Installation

Clone the repository:

git clone https://github.com/your-username/your-lms-repo.git
cd your-lms-repo

Set up a virtual environment:

python -m venv venv
source venv/bin/activate

Install dependencies:
```
pip install -r requirements.txt
```
Start the development server:
```
python manage.py runserver
```

Usage

Access the LMS dashboard at http://localhost:8000.
Create an account or log in as an admin to manage courses and users.
Explore the learning modules and track progress.

Contributors

Eric Mwaniki: [email protected]
Afelio Padilla: [email protected]

License

This project is licensed under the MIT License.

Acknowledgments

Special thanks to the Igniteus team for their support and collaboration on this project.

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Learning Management System (LMS)

Overview

Features

Technologies Used

Installation

Usage

Contributors

License

Acknowledgments

About

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Languages

Name		Name	Last commit message	Last commit date
Latest commit History 109 Commits
P2P5		P2P5
1_1_10_Loan_Eligibility_Prediction_.ipynb		1_1_10_Loan_Eligibility_Prediction_.ipynb
1_1_12_Churn_Prediction_for_Telecom (1).ipynb		1_1_12_Churn_Prediction_for_Telecom (1).ipynb
1_1_13_Basketball_Player_Performance_Prediction.ipynb		1_1_13_Basketball_Player_Performance_Prediction.ipynb
1_1_14_b_Energy_Consumption_Forecasting_Starter_Kit (1).ipynb		1_1_14_b_Energy_Consumption_Forecasting_Starter_Kit (1).ipynb
1_1_15_Vehicle_Price_Prediction.ipynb		1_1_15_Vehicle_Price_Prediction.ipynb
1_1_2_House_Price_Prediction_Starter_Kit.ipynb		1_1_2_House_Price_Prediction_Starter_Kit.ipynb
1_1_5_Sales_Forecasting.ipynb		1_1_5_Sales_Forecasting.ipynb
1_1_6_Wine_Quality_Prediction_Starter_Kit_.ipynb		1_1_6_Wine_Quality_Prediction_Starter_Kit_.ipynb
1_1_7_b_Bank_Marketing_Campaign_Analysis_Starter_Kit (1).ipynb		1_1_7_b_Bank_Marketing_Campaign_Analysis_Starter_Kit (1).ipynb
1_1_8_b_Diabetes_Prediction.ipynb		1_1_8_b_Diabetes_Prediction.ipynb
1_1_9_Heart_Disease_Prediction.ipynb		1_1_9_Heart_Disease_Prediction.ipynb
1_2_11_Hospital_Readmission_Prediction_Techniques_Applied_to_Iris_Species_Dataset.ipynb		1_2_11_Hospital_Readmission_Prediction_Techniques_Applied_to_Iris_Species_Dataset.ipynb
1_2_14_Healthcare_Cost_Prediction.ipynb		1_2_14_Healthcare_Cost_Prediction.ipynb
1_2_6_Drug_Bioactivity_Prediction_Starter_Kit (1).ipynb		1_2_6_Drug_Bioactivity_Prediction_Starter_Kit (1).ipynb
1_2_Analyzing_resumes_in_pdf_format.ipynb		1_2_Analyzing_resumes_in_pdf_format.ipynb
1_3_10_Predicting_Customer_Spending.ipynb		1_3_10_Predicting_Customer_Spending.ipynb
1_3_14_Customer_Attrition_in_Services.ipynb		1_3_14_Customer_Attrition_in_Services.ipynb
1_3_1_Customer_Segmentation_in_Retail.ipynb		1_3_1_Customer_Segmentation_in_Retail.ipynb
1_3_2_Churn_Prediction.ipynb		1_3_2_Churn_Prediction.ipynb
1_3_3_Customer_Lifetime_Value_Prediction.ipynb		1_3_3_Customer_Lifetime_Value_Prediction.ipynb
1_3_4_Market_Basket_Analysis.ipynb		1_3_4_Market_Basket_Analysis.ipynb
1_3_7_Insurance_Customer_Segmentation.ipynb		1_3_7_Insurance_Customer_Segmentation.ipynb
1_4_13_Real_Estate_Price_Prediction.ipynb		1_4_13_Real_Estate_Price_Prediction.ipynb
1_4_1_b_Credit_Card_Fraud_Detection_Starter_Kit.ipynb		1_4_1_b_Credit_Card_Fraud_Detection_Starter_Kit.ipynb
1_4_5_Portfolio_Management.ipynb		1_4_5_Portfolio_Management.ipynb
1_4_8_Algorithmic_Trading.ipynb		1_4_8_Algorithmic_Trading.ipynb
1_5_11_High_Frequency_Trading_(HFT)_Strategy.ipynb		1_5_11_High_Frequency_Trading_(HFT)_Strategy.ipynb
1_5_14_Foreign_Exchange_(Forex)_Trading_Strategy.ipynb		1_5_14_Foreign_Exchange_(Forex)_Trading_Strategy.ipynb
1_5_2_Mean_Reversion_Strategy.ipynb		1_5_2_Mean_Reversion_Strategy.ipynb
1_5_3_Momentum_Trading_Strategy.ipynb		1_5_3_Momentum_Trading_Strategy.ipynb
1_5_6_Volume_Weighted_Average_Price_(VWAP)_Strategy (1).ipynb		1_5_6_Volume_Weighted_Average_Price_(VWAP)_Strategy (1).ipynb
2_3_3_Guide_for_Image_Colorization_Using_CNNs.ipynb		2_3_3_Guide_for_Image_Colorization_Using_CNNs.ipynb
2_3_6_Facial_Expression_Recognition.ipynb		2_3_6_Facial_Expression_Recognition.ipynb
2_5_11_Automatic_Text_Generation_Actual.ipynb		2_5_11_Automatic_Text_Generation_Actual.ipynb
2_5_12_Resume_Screening.ipynb		2_5_12_Resume_Screening.ipynb
2_5_13_Medical_Transcription_Analysis.ipynb		2_5_13_Medical_Transcription_Analysis.ipynb
2_5_2_Spam_Email_Detection.ipynb		2_5_2_Spam_Email_Detection.ipynb
2_5_3_Named_Entity_Recognition_(NER).ipynb		2_5_3_Named_Entity_Recognition_(NER).ipynb
2_5_4_Text_Summarization_using_Sequence_to_Sequence_Model_with_Exploratory_Data_Analysis.ipynb		2_5_4_Text_Summarization_using_Sequence_to_Sequence_Model_with_Exploratory_Data_Analysis.ipynb
2_5_5_Topic_Modeling_for_Research_Articles.ipynb		2_5_5_Topic_Modeling_for_Research_Articles.ipynb
2_5_6_Language_Detection.ipynb		2_5_6_Language_Detection.ipynb
2_5_7_Fake_News_Detection.ipynb		2_5_7_Fake_News_Detection.ipynb
2_5_8_Chatbot_development_Starter_Kit.ipynb		2_5_8_Chatbot_development_Starter_Kit.ipynb
2_5_9_Emotion_Detection_in_Text.ipynb		2_5_9_Emotion_Detection_in_Text.ipynb
2_6_10_Crime_Hotspot_Prediction.ipynb		2_6_10_Crime_Hotspot_Prediction.ipynb
2_6_11_Optimizing_Emergency_Response_Routes.ipynb		2_6_11_Optimizing_Emergency_Response_Routes.ipynb
2_6_12_Wildlife_Habitat_Suitability_Modeling.ipynb		2_6_12_Wildlife_Habitat_Suitability_Modeling.ipynb
2_6_13_Solar_Energy_Potential_Mapping.ipynb		2_6_13_Solar_Energy_Potential_Mapping.ipynb
2_6_14_Water_Quality_Monitoring.ipynb		2_6_14_Water_Quality_Monitoring.ipynb
2_6_15_Agricultural_Crop_Yield_Predicti.ipynb		2_6_15_Agricultural_Crop_Yield_Predicti.ipynb
2_6_1_Land_use_classification.ipynb		2_6_1_Land_use_classification.ipynb
2_6_2_Geographic_Change_Detection.ipynb		2_6_2_Geographic_Change_Detection.ipynb
2_6_3_Enhancing_Satellite_Images.ipynb		2_6_3_Enhancing_Satellite_Images.ipynb
2_6_4_Modeling_Bike_Rides_Request.ipynb		2_6_4_Modeling_Bike_Rides_Request.ipynb
2_6_5_Transport_Demand_Modeling.ipynb		2_6_5_Transport_Demand_Modeling.ipynb
2_6_6_Predictive_Maintenance_of_Urban_Infrastructure.ipynb		2_6_6_Predictive_Maintenance_of_Urban_Infrastructure.ipynb
2_6_7_Urban_Heat_Island_Effect_Analysis.ipynb		2_6_7_Urban_Heat_Island_Effect_Analysis.ipynb
2_6_8_Flood_Risk_Prediction.ipynb		2_6_8_Flood_Risk_Prediction.ipynb
2_6_9_Air_Quality_Prediction.ipynb		2_6_9_Air_Quality_Prediction.ipynb
2_7_1_Generate_Anime_Characters_using_GANs_.ipynb		2_7_1_Generate_Anime_Characters_using_GANs_.ipynb
2_7_3_Abstractive_Text_Summarization_using_BART.ipynb		2_7_3_Abstractive_Text_Summarization_using_BART.ipynb
2_8_10_Synthetic_Corporate_Action_Data.ipynb		2_8_10_Synthetic_Corporate_Action_Data.ipynb
2_8_12_Synthetic_Insurance_Claim_Data.ipynb		2_8_12_Synthetic_Insurance_Claim_Data.ipynb
2_8_15_Synthetic_Financial_Sentiment_Data.ipynb		2_8_15_Synthetic_Financial_Sentiment_Data.ipynb
2_8_1_Stock_Price_Prediction_using_Time_Series_GANs.ipynb		2_8_1_Stock_Price_Prediction_using_Time_Series_GANs.ipynb
2_8_3_Fraud_Detection_using_Anomaly_Detection_GANs.ipynb		2_8_3_Fraud_Detection_using_Anomaly_Detection_GANs.ipynb
2_8_4_Synthetic_Credit_Risk_Scoring.ipynb		2_8_4_Synthetic_Credit_Risk_Scoring.ipynb
2_8_5_Portfolio_Optimization_with_Synthetic_Asset_Returns.ipynb		2_8_5_Portfolio_Optimization_with_Synthetic_Asset_Returns.ipynb
2_8_6_Synthetic_Trading_Data_Generation.ipynb		2_8_6_Synthetic_Trading_Data_Generation.ipynb
2_8_8_Synthetic_Customer_Transaction_Data.ipynb		2_8_8_Synthetic_Customer_Transaction_Data.ipynb
Ads_csv.ipynb		Ads_csv.ipynb
Adult_data_csv.ipynb		Adult_data_csv.ipynb
Adult_test_csv.ipynb		Adult_test_csv.ipynb
Adult_train_csv_.ipynb		Adult_train_csv_.ipynb
Analyzing_resumes_in_pdf_format.ipynb		Analyzing_resumes_in_pdf_format.ipynb
BERT_for_SA.ipynb		BERT_for_SA.ipynb
Beauty_csv.ipynb		Beauty_csv.ipynb
DistriBERT_for_SA.ipynb		DistriBERT_for_SA.ipynb
Dreamers_challenge.ipynb		Dreamers_challenge.ipynb
Flight_delays_test_csv.ipynb		Flight_delays_test_csv.ipynb
Graph_Analysis.ipynb		Graph_Analysis.ipynb
Improving_Sentiment_Analysis_on_Amazon_Reviews_with_Pre_trained_Models.ipynb		Improving_Sentiment_Analysis_on_Amazon_Reviews_with_Pre_trained_Models.ipynb
Joint - final_code (1) (1).ipynb		Joint - final_code (1) (1).ipynb
README.md		README.md
Reinforcement_Learning_for_Climate_Change_Mitigation_(ML,_Difficulty_9_10).ipynb		Reinforcement_Learning_for_Climate_Change_Mitigation_(ML,_Difficulty_9_10).ipynb
Sentiment_Analysis_on_the_Amazon_Reviews_Dataset_A_Comprehensive_Exploration (1).ipynb		Sentiment_Analysis_on_the_Amazon_Reviews_Dataset_A_Comprehensive_Exploration (1).ipynb
Text_Generation_Using_Markov_Chains_and_LSTM_Models.ipynb		Text_Generation_Using_Markov_Chains_and_LSTM_Models.ipynb
copy_of_1_1_7_b_bank_marketing_campaign_analysis_starter_kit.py		copy_of_1_1_7_b_bank_marketing_campaign_analysis_starter_kit.py
credit_scoring_sample_csv.ipynb		credit_scoring_sample_csv.ipynb
currency_csv_(3)_csv.ipynb		currency_csv_(3)_csv.ipynb
titanic_test_csv.ipynb		titanic_test_csv.ipynb
websites_test_sessions.ipynb		websites_test_sessions.ipynb

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