Learning Management System (LMS)

Overview

The Learning Management System (LMS) is a comprehensive platform designed to manage, deliver, and track educational courses and training programs. This project aims to revolutionize the education sector by providing an intuitive and efficient system for both learners and instructors. With a focus on user experience and powerful features, our LMS makes learning and teaching more effective and engaging.

Market Potential

The global e-learning market is projected to reach $325 billion by 2025, driven by the increasing adoption of digital learning solutions. Our LMS aims to capture a significant share of this market by offering unique features and superior user experience. We believe our solution can cater to a wide range of educational institutions, corporate training programs, and individual educators.

Unique Selling Points

User-Centric Design: Our platform offers an intuitive interface designed for seamless navigation and ease of use, ensuring a smooth learning experience for all users.
Advanced Analytics: We provide comprehensive tools for tracking and enhancing student performance, including detailed analytics and reporting capabilities.
Scalability: Our LMS is designed to easily scale to accommodate growing user bases and diverse learning needs, making it suitable for both small classes and large institutions.
Customization: Flexible and customizable to meet the unique needs of different educational settings, with support for various content types and learning methodologies.
Security: Robust security measures to protect user data and ensure privacy, complying with industry standards and regulations.

Roadmap

Q1 2024: Launch MVP with core features, including course management, user management, and basic analytics.
Q2 2024: Integrate advanced analytics and reporting tools to provide deeper insights into student performance.
Q3 2024: Expand course offerings and add multilingual support to cater to a global audience.
Q4 2024: Launch a mobile app to enhance accessibility and expand to international markets, focusing on regions with high growth potential in e-learning.

Installation

Follow these steps to set up the LMS locally:

Clone the repository:

git clone https://github.com/Eric428-a/-LMS-Learning-Management-System.git
cd -LMS-Learning-Management-System

## Contat me at;  [email protected]

Provide feedback

Saved searches

Use saved searches to filter your results more quickly

Repository files navigation

Learning Management System (LMS)

Overview

Market Potential

Unique Selling Points

Roadmap

Installation

About

Releases

Packages

Languages

Name		Name	Last commit message	Last commit date
Latest commit History 183 Commits
healthcare		healthcare
1_1_10_Loan_Eligibility_Prediction_.ipynb		1_1_10_Loan_Eligibility_Prediction_.ipynb
1_1_12_Churn_Prediction_for_Telecom.ipynb		1_1_12_Churn_Prediction_for_Telecom.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.ipynb		1_1_14_b_Energy_Consumption_Forecasting_Starter_Kit.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.ipynb		1_1_7_b_Bank_Marketing_Campaign_Analysis_Starter_Kit.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_12_Patient_length_of_sttay_prediction_–_Starter_Kit.ipynb		1_2_12_Patient_length_of_sttay_prediction_–_Starter_Kit.ipynb
1_2_14_Healthcare_Cost_Prediction.ipynb		1_2_14_Healthcare_Cost_Prediction.ipynb
1_2_15_Patient_No_show_Prediction_using_Gradient_Boosting_Machines_(GBM)_Starter_Kit.ipynb		1_2_15_Patient_No_show_Prediction_using_Gradient_Boosting_Machines_(GBM)_Starter_Kit.ipynb
1_2_1_b_Diabetes_Prediction_Starter_Kit.ipynb		1_2_1_b_Diabetes_Prediction_Starter_Kit.ipynb
1_2_2_b_Heart_Disease_Prediction_using_Decision_Trees_Starter_Kit.ipynb		1_2_2_b_Heart_Disease_Prediction_using_Decision_Trees_Starter_Kit.ipynb
1_2_3_Breast_Cancer_Detection_using_SVM_Starter_Kit.ipynb		1_2_3_Breast_Cancer_Detection_using_SVM_Starter_Kit.ipynb
1_2_4_Liver_Disease_Prediction_using_Random_Forest_Starter_Kit.ipynb		1_2_4_Liver_Disease_Prediction_using_Random_Forest_Starter_Kit.ipynb
1_2_6_Drug_Bioactivity_Prediction_Starter_Kit.ipynb		1_2_6_Drug_Bioactivity_Prediction_Starter_Kit.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_4_b_Stock_Price_Prediction_Starter_Kit.ipynb		1_4_4_b_Stock_Price_Prediction_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_10_b_Risk_Management_Strategy_Starter_Kit.ipynb		1_5_10_b_Risk_Management_Strategy_Starter_Kit.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_1_b_Moving_Average_Crossover_Strategy.ipynb		1_5_1_b_Moving_Average_Crossover_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.ipynb		1_5_6_Volume_Weighted_Average_Price_(VWAP)_Strategy.ipynb
1_5_9_Statistical_Arbitrage_Strategy_Using_PCA_–_Starter_Kit.ipynb		1_5_9_Statistical_Arbitrage_Strategy_Using_PCA_–_Starter_Kit.ipynb
2_1_9_b_Heart_Disease_Prediction_using_Random_Forest_Starter_Kit.ipynb		2_1_9_b_Heart_Disease_Prediction_using_Random_Forest_Starter_Kit.ipynb
2_3_3_Guide_for_Image_Colorization_Using_CNNs.ipynb		2_3_3_Guide_for_Image_Colorization_Using_CNNs.ipynb
2_3_4_Hand_Gesture_Recognition_Starter_Kit.ipynb		2_3_4_Hand_Gesture_Recognition_Starter_Kit.ipynb
2_3_5_b_Road_Lane_Detection_for_Autonomous_Vehicles_using_Hough_Transform_Starter_Kit.ipynb		2_3_5_b_Road_Lane_Detection_for_Autonomous_Vehicles_using_Hough_Transform_Starter_Kit.ipynb
2_5_11_Automatic_Text_Generation.ipynb		2_5_11_Automatic_Text_Generation.ipynb
2_5_11_Automatic_Text_Generation_Actual.ipynb		2_5_11_Automatic_Text_Generation_Actual.ipynb
2_5_15_a_Customer_Feedback_Analysis_Starter_Kit.ipynb		2_5_15_a_Customer_Feedback_Analysis_Starter_Kit.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_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
Affairs_csv.ipynb		Affairs_csv.ipynb
Air_Quality_Forecasting_with_Regression_Models.ipynb		Air_Quality_Forecasting_with_Regression_Models.ipynb
Analyzing_resumes_in_pdf_format.ipynb		Analyzing_resumes_in_pdf_format.ipynb
BERT_for_SA.ipynb		BERT_for_SA.ipynb
CREDIT_SCORING_USING_LOGISTIC_REGRESSION.ipynb		CREDIT_SCORING_USING_LOGISTIC_REGRESSION.ipynb
Copy_of_1_1_14_b_Energy_Consumption_Forecasting_Starter_Kit.ipynb		Copy_of_1_1_14_b_Energy_Consumption_Forecasting_Starter_Kit.ipynb
Copy_of_1_1_7_b_Bank_Marketing_Campaign_Analysis_Starter_Kit.ipynb		Copy_of_1_1_7_b_Bank_Marketing_Campaign_Analysis_Starter_Kit.ipynb
Copy_of_Fashion_MNIST_Image_Classification_with_Convolutional_Neural_Networks.ipynb		Copy_of_Fashion_MNIST_Image_Classification_with_Convolutional_Neural_Networks.ipynb
DistriBERT_for_SA.ipynb		DistriBERT_for_SA.ipynb
Eric FUNDING.yml		Eric FUNDING.yml
Fashion_MNIST_Image_Classification_with_Convolutional_Neural_Networks.ipynb		Fashion_MNIST_Image_Classification_with_Convolutional_Neural_Networks.ipynb
Improving_Sentiment_Analysis_on_Amazon_Reviews_with_Pre_trained_Models.ipynb		Improving_Sentiment_Analysis_on_Amazon_Reviews_with_Pre_trained_Models.ipynb
Linear_regression_for_wine_quality_dataset.ipynb		Linear_regression_for_wine_quality_dataset.ipynb
Possible_Tasks_from_telecom_churn_csv.ipynb		Possible_Tasks_from_telecom_churn_csv.ipynb
Possible_tasks_from_hostel_factors_csv.ipynb		Possible_tasks_from_hostel_factors_csv.ipynb
Possible_tasks_from_medium_posts_csv.ipynb		Possible_tasks_from_medium_posts_csv.ipynb
Possible_tasks_fromflight_delays_train_csv.ipynb		Possible_tasks_fromflight_delays_train_csv.ipynb
README.md		README.md
Sentiment_Analysis_on_the_Amazon_Reviews_Dataset_A_Comprehensive_Exploration.ipynb		Sentiment_Analysis_on_the_Amazon_Reviews_Dataset_A_Comprehensive_Exploration.ipynb
Some_possible_tasks_from_mlbootcamp5_train_csv.ipynb		Some_possible_tasks_from_mlbootcamp5_train_csv.ipynb
Text_Generation_Using_Markov_Chains_and_LSTM_Models.ipynb		Text_Generation_Using_Markov_Chains_and_LSTM_Models.ipynb
Titanic_train_csv.ipynb		Titanic_train_csv.ipynb
Weights_heights_1.ipynb		Weights_heights_1.ipynb
Wine_Quality.ipynb		Wine_Quality.ipynb
_config.yml		_config.yml
accidental_deaths_in_usa_monthly_csv.ipynb		accidental_deaths_in_usa_monthly_csv.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
beauty_csv.ipynb		beauty_csv.ipynb
credit_scoring_sample_csv.ipynb		credit_scoring_sample_csv.ipynb
currency_csv_(3)_csv.ipynb		currency_csv_(3)_csv.ipynb
flight_delays_test_csv.ipynb		flight_delays_test_csv.ipynb
titanic_test_csv.ipynb		titanic_test_csv.ipynb
websites_test_sessions.ipynb		websites_test_sessions.ipynb

Eric428-a/-LMS-Learning-Management-System

Folders and files

Latest commit

History

Repository files navigation

Learning Management System (LMS)

Overview

Market Potential

Unique Selling Points

Roadmap

Installation

About

Resources

Stars

Watchers

Forks

Releases

Packages 0

Languages

Packages