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README.md

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----
-title: DS Webclass
-emoji: 🏆
-colorFrom: gray
-colorTo: red
-sdk: streamlit
-sdk_version: 1.44.1
-app_file: app.py
-pinned: false
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+# Data Science Course App
+
+An interactive Streamlit-based platform for guiding students through a 10-week machine learning research paper project.
+
+## Project Structure
+
+```
+DS_course_app/
+├── app/
+│   ├── pages/           # Individual week pages
+│   ├── components/      # Reusable Streamlit components
+│   └── utils/          # Utility functions
+├── data/               # Sample datasets and resources
+├── assets/            # Images, CSS, and other static files
+├── environment.yml    # Conda environment file
+└── requirements.txt   # Project dependencies (alternative)
+```
+
+## Setup Instructions
+
+1. Create and activate the Conda environment:
+```bash
+# Create the environment from environment.yml
+conda env create -f environment.yml
+
+# Activate the environment
+conda activate ds_course_app
+```
+
+2. Run the application:
+```bash
+streamlit run app/main.py
+```
+
+## Course Structure
+
+The course is designed to guide students through the process of creating a machine learning research paper over 10 weeks:
+
+1. Week 1: Research Topic Selection and Literature Review
+2. Week 2: Data Collection and Preprocessing
+3. Week 3: Exploratory Data Analysis
+4. Week 4: Feature Engineering
+5. Week 5: Model Selection and Baseline
+6. Week 6: Model Training and Optimization
+7. Week 7: Model Evaluation
+8. Week 8: Results Analysis
+9. Week 9: Paper Writing
+10. Week 10: Final Review and Submission
+
+## Features
+
+- Interactive learning modules for each week
+- Progress tracking
+- Sample datasets and resources
+- Code templates and examples
+- Peer review system
+- Submission and feedback system
+
+## Environment Management
+
+### Using Conda (Recommended)
+```bash
+# Create environment
+conda env create -f environment.yml
+
+# Activate environment
+conda activate ds_course_app
+
+# Update environment
+conda env update -f environment.yml
+
+# Deactivate environment
+conda deactivate
+```
+
+### Alternative: Using pip
+If you prefer using pip, you can still use the requirements.txt file:
+```bash
+pip install -r requirements.txt
+``` 

app.py

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+import streamlit as st
+import os
+import sys
+
+# Add the current directory to the Python path
+sys.path.append(os.path.dirname(os.path.abspath(__file__)))
+
+# Import the main app
+from app.main import main, sidebar_navigation, load_css
+
+if __name__ == "__main__":
+    load_css()
+    sidebar_navigation()
+    main() 

app/__init__.py

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+# This file makes the app directory a Python package 

app/components/__init__.py

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+# This file makes the components directory a Python package 

app/components/login.py

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+import streamlit as st
+
+def login():
+    """
+    Display a login form and return True if login is successful, False otherwise.
+    """
+    st.title("Login to Data Science Course App")
+    
+    # Create a form for login
+    with st.form("login_form"):
+        username = st.text_input("Username")
+        password = st.text_input("Password", type="password")
+        submit_button = st.form_submit_button("Login")
+        
+        if submit_button:
+            # Check credentials (test account)
+            if username == "student" and password == "123":
+                # Store login state in session
+                st.session_state.logged_in = True
+                st.session_state.username = username
+                st.success("Login successful!")
+                st.rerun()
+            else:
+                st.error("Invalid username or password. Please try again.")
+    
+    return st.session_state.get("logged_in", False) 

app/main.py

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+import streamlit as st
+import os
+import glob
+import sys
+
+# Add the parent directory to the Python path
+sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
+
+# Import the login component
+from app.components.login import login
+
+# Page configuration
+st.set_page_config(
+    page_title="Data Science Course App",
+    page_icon="📚",
+    layout="wide",
+    initial_sidebar_state="expanded"
+)
+
+# Custom CSS
+def load_css():
+    try:
+        with open('assets/style.css') as f:
+            st.markdown(f'<style>{f.read()}</style>', unsafe_allow_html=True)
+    except FileNotFoundError:
+        # Fallback for Streamlit Cloud deployment
+        st.markdown("""
+        <style>
+        /* Main title styling */
+        .main .block-container h1 {
+            color: #2c3e50;
+            font-size: 2.5rem;
+            margin-bottom: 1rem;
+        }
+        
+        /* Subtitle styling */
+        .main .block-container h2 {
+            color: #34495e;
+            font-size: 1.8rem;
+            margin-top: 2rem;
+            margin-bottom: 1rem;
+        }
+        
+        /* Sidebar styling */
+        .sidebar .sidebar-content {
+            background-color: #f8f9fa;
+        }
+        
+        /* Button styling */
+        .stButton>button {
+            width: 100%;
+            border-radius: 5px;
+            height: 3em;
+            margin: 0.5em 0;
+            background-color: #3498db;
+            color: white;
+            border: none;
+        }
+        
+        .stButton>button:hover {
+            background-color: #2980b9;
+        }
+        
+        /* Progress bar styling */
+        .stProgress > div > div {
+            background-color: #2ecc71;
+        }
+        
+        /* Info box styling */
+        .stAlert {
+            border-radius: 5px;
+            padding: 1rem;
+            margin: 1rem 0;
+        }
+        
+        /* Code block styling */
+        .stCodeBlock {
+            background-color: #f8f9fa;
+            border-radius: 5px;
+            padding: 1rem;
+            margin: 1rem 0;
+        }
+        </style>
+        """, unsafe_allow_html=True)
+
+# Initialize session state
+if 'current_week' not in st.session_state:
+    st.session_state.current_week = 1
+if 'logged_in' not in st.session_state:
+    st.session_state.logged_in = False
+
+# Get class content
+def get_class_content(week_number):
+    # Try different possible paths for class files
+    possible_paths = [
+        f"data_science_class_files/class_{week_number}",  # Local development
+        f"app/data_science_class_files/class_{week_number}",  # Alternative local path
+        f"class_{week_number}",  # Streamlit Cloud deployment
+    ]
+    
+    for class_dir in possible_paths:
+        if os.path.exists(class_dir):
+            # Get all files in the class directory
+            files = glob.glob(f"{class_dir}/*")
+            return {
+                'directory': class_dir,
+                'files': [os.path.basename(f) for f in files]
+            }
+    
+    return None
+
+# Sidebar navigation
+def sidebar_navigation():
+    with st.sidebar:
+        st.title("Course Navigation")
+        
+        # Show username if logged in
+        if st.session_state.logged_in:
+            st.write(f"Welcome, {st.session_state.username}!")
+            
+            # Logout button
+            if st.button("Logout"):
+                st.session_state.logged_in = False
+                st.session_state.username = None
+                st.rerun()
+        
+        st.markdown("---")
+        st.subheader("Course Progress")
+        progress = st.progress(st.session_state.current_week / 10)
+        st.write(f"Week {st.session_state.current_week} of 10")
+        
+        st.markdown("---")
+        st.subheader("Quick Links")
+        for week in range(1, 11):
+            if st.button(f"Week {week}", key=f"week_{week}"):
+                st.session_state.current_week = week
+                st.rerun()
+
+# Main content
+def main():
+    # Check if user is logged in
+    if not st.session_state.logged_in:
+        # Show login page
+        login()
+        return
+    
+    # User is logged in, show course content
+    st.title("Data Science Research Paper Course")
+    
+    # Welcome message for first-time visitors
+    if st.session_state.current_week == 1:
+        st.markdown("""
+        ## Welcome to the Data Science Research Paper Course! 📚
+        
+        This 10-week course will guide you through the process of creating a machine learning research paper.
+        Each week, you'll learn new concepts and complete tasks that build upon each other.
+        
+        ### Getting Started
+        1. Use the sidebar to navigate between weeks
+        2. Complete the weekly tasks and assignments
+        3. Track your progress using the progress bar
+        4. Submit your work for feedback
+        
+        ### Course Overview
+        - Week 1: Research Topic Selection and Literature Review
+        - Week 2: Data Collection and Preprocessing
+        - Week 3: Exploratory Data Analysis
+        - Week 4: Feature Engineering
+        - Week 5: Model Selection and Baseline
+        - Week 6: Model Training and Optimization
+        - Week 7: Model Evaluation
+        - Week 8: Results Analysis
+        - Week 9: Paper Writing
+        - Week 10: Final Review and Submission
+        """)
+    
+    # Display current week's content
+    st.markdown(f"## Week {st.session_state.current_week}")
+    
+    # Get class content
+    class_content = get_class_content(st.session_state.current_week)
+    
+    if class_content:
+        st.subheader("Class Materials")
+        
+        # Display files in the class directory
+        for file in class_content['files']:
+            file_path = os.path.join(class_content['directory'], file)
+            
+            # Handle different file types
+            if file.endswith('.py'):
+                try:
+                    with open(file_path, 'r') as f:
+                        st.code(f.read(), language='python')
+                except Exception as e:
+                    st.error(f"Error reading file {file}: {str(e)}")
+            elif file.endswith('.md'):
+                try:
+                    with open(file_path, 'r') as f:
+                        st.markdown(f.read())
+                except Exception as e:
+                    st.error(f"Error reading file {file}: {str(e)}")
+            elif file.endswith(('.pptx', '.pdf', '.doc', '.docx')):
+                try:
+                    with open(file_path, 'rb') as f:
+                        st.download_button(
+                            label=f"Download {file}",
+                            data=f.read(),
+                            file_name=file,
+                            mime='application/octet-stream'
+                        )
+                except Exception as e:
+                    st.error(f"Error reading file {file}: {str(e)}")
+            else:
+                st.write(f"- {file}")
+    else:
+        st.info("Content for this week is being prepared. Check back soon!")
+
+if __name__ == "__main__":
+    load_css()
+    sidebar_navigation()
+    main() 

app/pages/week_1.py

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+import streamlit as st
+
+def show_week_content():
+    st.markdown("""
+    ## Week 1: Research Topic Selection and Literature Review
+    
+    This week, you'll learn how to:
+    - Select a suitable research topic
+    - Conduct a literature review
+    - Define your research objectives
+    - Create a research proposal
+    """)
+    
+    # Topic Selection Section
+    st.header("1. Topic Selection")
+    st.markdown("""
+    ### Guidelines for Selecting Your Research Topic:
+    - Choose a topic that interests you
+    - Ensure sufficient data availability
+    - Consider the scope and complexity
+    - Check for existing research gaps
+    """)
+    
+    # Interactive Topic Selection
+    st.subheader("Topic Selection Form")
+    with st.form("topic_form"):
+        research_area = st.selectbox(
+            "Select your research area",
+            ["Computer Vision", "NLP", "Time Series", "Recommendation Systems", "Other"]
+        )
+        
+        topic = st.text_input("Proposed Research Topic")
+        problem_statement = st.text_area("Brief Problem Statement")
+        motivation = st.text_area("Why is this research important?")
+        
+        submitted = st.form_submit_button("Submit Topic")
+        
+        if submitted:
+            st.success("Topic submitted successfully! We'll review and provide feedback.")
+    
+    # Literature Review Section
+    st.header("2. Literature Review")
+    st.markdown("""
+    ### Steps for Conducting Literature Review:
+    1. Search for relevant papers
+    2. Read and analyze key papers
+    3. Identify research gaps
+    4. Document your findings
+    """)
+    
+    # Literature Review Template
+    st.subheader("Literature Review Template")
+    with st.expander("Download Template"):
+        st.download_button(
+            label="Download Literature Review Template",
+            data="Literature Review Template\n\n1. Introduction\n2. Related Work\n3. Methodology\n4. Results\n5. Discussion\n6. Conclusion",
+            file_name="literature_review_template.txt",
+            mime="text/plain"
+        )
+    
+    # Weekly Assignment
+    st.header("Weekly Assignment")
+    st.markdown("""
+    ### Assignment 1: Research Proposal
+    1. Select your research topic
+    2. Write a brief problem statement
+    3. Conduct initial literature review
+    4. Submit your research proposal
+    
+    **Due Date:** End of Week 1
+    """)
+    
+    # Assignment Submission
+    st.subheader("Submit Your Assignment")
+    with st.form("assignment_form"):
+        proposal_file = st.file_uploader("Upload your research proposal (PDF or DOC)")
+        comments = st.text_area("Additional comments or questions")
+        
+        if st.form_submit_button("Submit Assignment"):
+            if proposal_file is not None:
+                st.success("Assignment submitted successfully!")
+            else:
+                st.error("Please upload your research proposal.")
+
+if __name__ == "__main__":
+    show_week_content() 

assets/style.css

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+/* Main title styling */
+.main .block-container h1 {
+    color: #2c3e50;
+    font-size: 2.5rem;
+    margin-bottom: 1rem;
+}
+
+/* Subtitle styling */
+.main .block-container h2 {
+    color: #34495e;
+    font-size: 1.8rem;
+    margin-top: 2rem;
+    margin-bottom: 1rem;
+}
+
+/* Sidebar styling */
+.sidebar .sidebar-content {
+    background-color: #f8f9fa;
+}
+
+/* Button styling */
+.stButton>button {
+    width: 100%;
+    border-radius: 5px;
+    height: 3em;
+    margin: 0.5em 0;
+    background-color: #3498db;
+    color: white;
+    border: none;
+}
+
+.stButton>button:hover {
+    background-color: #2980b9;
+}
+
+/* Progress bar styling */
+.stProgress > div > div {
+    background-color: #2ecc71;
+}
+
+/* Info box styling */
+.stAlert {
+    border-radius: 5px;
+    padding: 1rem;
+    margin: 1rem 0;
+}
+
+/* Code block styling */
+.stCodeBlock {
+    background-color: #f8f9fa;
+    border-radius: 5px;
+    padding: 1rem;
+    margin: 1rem 0;
+} 

environment.yml

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+name: ds_course_app
+channels:
+  - conda-forge
+  - defaults
+dependencies:
+  - python=3.11
+  - streamlit=1.32.0
+  - pandas=2.2.0
+  - numpy=1.26.4
+  - scikit-learn=1.4.0
+  - matplotlib=3.8.3
+  - seaborn=0.13.2
+  - plotly=5.18.0
+  - pip
+  - pip:
+    - streamlit==1.32.0  # Some packages might need to be installed via pip 

requirements.txt

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+streamlit==1.32.0
+pandas==2.2.0
+numpy==1.26.4
+scikit-learn==1.4.0
+matplotlib==3.8.3
+seaborn==0.13.2
+plotly==5.18.0