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REQUIREMENT_ID_1563 β€’ 3-DAY_ACTIVE_POLICY

Python Internship

Company
Company Learntricks Edutech
Type
Opportunity Type Internship
Salary
Stipend / Salary β‚Ή12,000 - β‚Ή15,000 per month
Location
Location Remote
Posted Date
Posted Date Today
HTML CSS JavaScript Angular React jQuery Python Django Node.js PHP
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Aptitude and Reasoning Practice Open Resource β†—
Helps sharpen logical thinking and problem‑solving skills essential for coding interviews.
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Company Interview Preparation Open Resource β†—
Provides insights into common interview questions and interview patterns for tech roles.
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Internship Experience Insights Open Resource β†—
Offers real‑world scenarios and case studies relevant to internship projects.
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Coding Practice Problems Open Resource β†—
Offers a wide range of coding challenges to improve algorithmic thinking and Python proficiency.

Undergraduate or Postgraduate students from Engineering, Arts, Commerce, Sciences, or Management disciplines. Minimum 50% in 10th/12th/Graduation. No backlog allowed. Letter of recommendation accepted.

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Round 1: Technical screening
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Round 2: Technical interview
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Round 3: HR
Learntricks Edutech is a rapidly growing edutech startup that focuses on delivering high-quality online learning solutions to students across India. With a mission to democratise education, the company has built a robust platform that offers interactive courses, live mentorship, and AI‑driven personalized learning paths. The team is composed of passionate educators, software engineers, and data scientists who collaborate to create engaging content and cutting‑edge technology. The Python Internship role is designed for enthusiastic college students who want to gain hands‑on experience in full‑stack development. Interns will be integrated into the development lifecycle, contributing to both front‑end and back‑end components of the platform. The role requires a blend of coding, problem‑solving, and teamwork, making it an ideal stepping stone for future software engineers. Key Responsibilities: 1. Participate in all phases of the software development lifecycle. 2. Write clean, efficient, and well‑documented code. 3. Design high‑volume, low‑latency applications. 4. Develop responsive front‑end interfaces using HTML, CSS, JavaScript. 5. Implement modern UI frameworks such as Angular, React, or jQuery. 6. Build and maintain back‑end services using Python, Django, Node.js, or PHP. 7. Collaborate with cross‑functional teams to gather requirements. 8. Conduct unit and integration testing. 9. Optimize application performance and troubleshoot issues. 10. Participate in code reviews and knowledge sharing sessions. Tech Stack: HTML, CSS, JavaScript, Angular, React, jQuery, Python, Django, Node.js, PHP. Growth Path: Interns who demonstrate strong technical skills and a proactive attitude may be offered a full‑time role as a Junior Software Engineer or a Product Engineer. The company values continuous learning and offers mentorship, workshops, and opportunities to work on diverse projects. Why Join: Learntricks Edutech offers a collaborative environment, exposure to real‑world projects, and the chance to impact millions of learners. Interns receive a competitive stipend, flexible work hours, and the opportunity to work remotely. The company culture encourages innovation, open communication, and a healthy work‑life balance, making it an attractive place for fresh talent to grow.

Learntricks Edutech β€” AI & Machine Learning Interview Guide

Previously asked questions, exam syllabus, coding benchmarks & round strategy.

APTITUDE & LOGIC πŸ“–
Aptitude Practice Questions & Online Mock Tests

Curated logical, quantitative, and verbal reasoning problems to sharpen reasoning skills required for the initial screening test.

Open Resource β†—
COMPANY GUIDE 🎯
Learntricks Edutech Interview Preparation Corner

Comprehensive guide covering typical interview formats, common questions, and preparation tips for Learntricks Edutech and off-campus tech roles.

Open Resource β†—
MOCK TESTS & PAPERS πŸ“
Comprehensive Interview Prep Resources & Syllabus

Collection of previous year questions, company-specific test patterns, and interview experiences for technical and HR rounds.

Open Resource β†—
CODING PRACTICE πŸ’»
Algorithm and Data Structure Problem Set

Practice problems to improve coding proficiency and algorithm problem-solving speed for technical rounds.

Open Resource β†—
Round 1: Online Assessment (OA)
Aptitude, Quantitative Logic & 2 Coding Problems
Focus on accuracy and speed. Practice arrays, strings, and standard arithmetic puzzles.
Round 2: Technical Interview 1
Core Tech Stack (HTML, CSS, JavaScript, Angular, React, jQuery, Python, Django, Node.js, PHP) & Live Code Tracing
Explain your thought process aloud. Analyze time & space complexities before coding.
Round 3: System Design & Problem Solving
Database Schemas, APIs & Architecture Basics
Clarify edge cases, diagram schemas cleanly, and discuss scalability trade-offs.
Round 4: HR & Cultural Fit Discussion
Learntricks Edutech Core Values, Learning Agility & Offer Terms
Demonstrate passion, strong communication, and readiness for full-time collaboration.
What is the bias-variance tradeoff and how do you prevent overfitting? Answer β–Ό
Model Answer: High bias leads to underfitting (oversimplified model), high variance leads to overfitting (captures noise). Mitigate using L1/L2 Regularization, Dropout, Cross-Validation, and data augmentation.
Explain the difference between Precision, Recall, and F1-Score. Answer β–Ό
Model Answer: Precision = TP / (TP + FP) (correctness of positive predictions). Recall = TP / (TP + FN) (coverage of actual positives). F1-Score is the harmonic mean of Precision and Recall.
How does Gradient Descent work and what is the role of Learning Rate? Answer β–Ό
Model Answer: It optimizes loss functions by iteratively moving weights in the direction of negative gradient. A large learning rate may overshoot the minimum; a small rate causes slow convergence.
What is the difference between Supervised, Unsupervised, and Self-Supervised learning? Answer β–Ό
Model Answer: Supervised uses labeled data (X -> y). Unsupervised finds hidden patterns in unlabeled data (clustering/PCA). Self-supervised generates labels from input data (e.g. masked language modeling in BERT/Transformers).
Why do you want to join Learntricks Edutech as a Python Internship?
Preparation Tip: Highlight Learntricks Edutech's market reputation, recent tech innovations, and how your skills in HTML directly solve their team's objectives.
Describe a challenging bug or academic project roadblock and how you resolved it.
Preparation Tip: Use the STAR method: Situation (project context), Task (what needed solving), Action (specific tools/logic applied), Result (quantifiable positive outcome).
How do you handle strict deadlines or sudden scope changes?
Preparation Tip: Explain your prioritization strategy, proactive communication with mentors/peers, and agile mindset.

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