        1. Roles & Responsibilities: 2/10  
        2. Years of Experience: 4/10  
        3. Education Qualification: 8/10  
        4. Skills/Knowledge: 4/10  
        5. Domain/Industry: 4/10  
        6. Key Competencies: 4/10  
        7. Certifications: 4/10  

```html
<h5 style="font-family:Roboto; font-size:0.88rem; font-weight:bold;">Overall Summary</h5>
<ol style="font-family:Roboto; font-size:0.88rem;">
    <li>The candidate's experience does not align well with the specified roles and responsibilities. While the resume demonstrates experience in machine learning and AI projects, it lacks evidence of data engineering tasks such as designing and maintaining data pipelines, data cleaning, transformation, validation, or creating dashboards and visualizations.</li>
    <li>Years of experience are partially relevant. The candidate has multiple internships, but they are primarily focused on machine learning and AI rather than data engineering. The experience duration is within the 0-1 year range, but the relevance to the job requirements is limited.</li>
    <li>The educational qualification is a strong match. The candidate is pursuing a Bachelor of Technology in Computer Science with a specialization in AI & ML, which aligns with the requirement for a BE or equivalent in Computer Science or related disciplines.</li>
    <li>The skills section shows some overlap with the required skills. The candidate has Python experience (including Pandas, Matplotlib, and Seaborn) and MySQL knowledge. However, there is no mention of Power BI or Excel, which are critical for the role. The focus on machine learning frameworks like TensorFlow and PyTorch is less relevant to the job requirements.</li>
    <li>The domain knowledge is partially relevant. The candidate has experience in AI and machine learning, which are adjacent to data engineering but not directly aligned with the IT/Data Engineering domain specified in the job requirements.</li>
    <li>Key competencies such as problem-solving, communication, and adaptability are mentioned but not demonstrated in the context of data engineering tasks. The resume lacks evidence of collaboration with cross-functional teams, workflow documentation, or articulating technical concepts to non-technical stakeholders.</li>
    <li>The certifications listed are relevant to machine learning and AI but do not align with the required certifications for Python, MySQL, Power BI, or Excel. This limits the candidate's fitment for the role.</li>
</ol>
```