Write clean, efficient, and well-documented Python code for projects and assignments. Work on real-world applications such as data processing, automation, or backend development. Learn and apply concepts of Object-Oriented Programming (OOP) , data manipulation , and API integration . Collaborate with mentors to debug, test, and optimize your code. Work with libraries like NumPy, Pandas, and Matplotlib for data handling and visualization. Participate in weekly mentor review sessions and share progress on GitHub. Assist in developing mini-projects and capstone projects under supervision. What Youll Gain Real-time project exposure and coding experience. Mentorship and guidance from industry professionals. Internship Certificate from NeoSkillz upon successful completion. Performance-based stipend (up to 15,000). Resume-building experience with GitHub portfolio and project documentation.
Role & responsibilities Collect, clean, and preprocess datasets. Perform exploratory data analysis and visualize insights. Develop and evaluate machine learning models. Assist in building basic deep learning models (optional). Optimize algorithms and perform hyperparameter tuning. Document work, maintain Git repositories, and collaborate with the team. Support model deployment and integration tasks as needed. Preferred candidate profile
1. Model Development & Fine-Tuning Develop, train, and fine-tune Generative AI models (LLMs, diffusion models, RAG pipelines, etc.) Optimize models for performance, accuracy, and scalability Implement prompt engineering and advanced generation techniques 2. Data Preparation & Management Curate, clean, and preprocess large datasets for generative tasks Build and maintain datasets for text, image, audio, or multimodal AI Ensure data privacy compliance (GDPR, internal data policies) 3. System Integration Integrate generative AI models into applications, APIs, or product workflows Work with backend, frontend, and DevOps teams for deployment Build scalable inference pipelines using cloud platforms (AWS, GCP, Azure) 4. Research & Innovation Evaluate new LLMs, frameworks, and model architectures Experiment with emerging GenAI technologies (RAG, agent workflows, model distillation) Create PoCs and prototypes for internal and client-facing use cases
Role & responsibilities Collect, clean, and preprocess datasets for analysis Perform exploratory data analysis (EDA) to uncover trends and patterns Assist in building dashboards and reports using tools like Excel, Google Sheets, Power BI, or Tableau Support the team by preparing data visualizations and presentations Work with analytics leads to identify business insights and recommendations Document findings, workflows, and analysis results clearly Collaborate with cross-functional teams on ongoing data-related projects Stay updated with current analytics tools, techniques, and best practices Preferred Candidate Profile Basic knowledge of statistics, data analysis, and problem-solving Familiarity with tools like Excel, SQL, Python, or data visualization platforms Understanding of data cleaning, EDA, and basic reporting concepts Strong analytical thinking and attention to detail Good communication skills to explain insights clearly Ability to work independently and meet deadlines Passion for learning and applying data analytics in real-world scenarios Prior academic projects or certifications in Data Analytics (preferred but not mandatory)
Responsibilities Write clean, efficient, and reusable Python code Develop, test, and maintain backend applications using Python frameworks (Django/Flask/FastAPI) Design and manage scalable database structures and APIs Integrate front-end elements with server-side logic Debug and troubleshoot issues to improve performance and reliability Collaborate with cross-functional teams (UI/UX, QA, DevOps) Work with version control systems like Git for code reviews and collaborative development Implement security protocols, authentication, and authorization Create automation scripts and tools as required Qualifications & Skills Strong foundation in Python programming Experience with Django , Flask , or FastAPI (any one is sufficient for entry-level) Knowledge of databases such as MySQL , PostgreSQL , or MongoDB Understanding of RESTful API design and integration Familiarity with HTML, CSS, JavaScript (basic understanding) Good understanding of OOPs , MVC architecture, and clean coding principles Knowledge of Git, GitHub, and basic CI/CD workflows Strong analytical and problem-solving skills
Role & responsibilities Your key responsibilities include: Collecting, cleaning, and analyzing structured and unstructured data. Performing exploratory data analysis (EDA) to identify patterns and insights. Building and evaluating machine learning models for predictive analytics. Working with tools and libraries such as Python, Pandas, NumPy, Matplotlib, and Scikit-learn . Collaborating with mentors and team members to deliver project reports and dashboards. Presenting findings and visualizations effectively using tools like Power BI or Tableau . Supporting ongoing data projects and contributing to innovation initiatives within the team. Preferred candidate profile
Role & responsibilities Design, develop, test, and deploy scalable web applications using front-end and back-end technologies Build responsive and user-friendly UI components using HTML, CSS, JavaScript, and modern frameworks Develop robust server-side logic and RESTful APIs Integrate databases and ensure efficient data storage and retrieval Collaborate with designers, product managers, and other developers to deliver high-quality solutions Write clean, maintainable, and reusable code following best practices Perform debugging, testing, and performance optimization Ensure application security, scalability, and reliability Participate in code reviews and follow version control practices (Git/GitHub) Stay updated with emerging technologies and industry trends Bachelors degree in Computer Science, Engineering, or related field (or equivalent practical experience) Strong knowledge of front-end technologies : HTML, CSS, JavaScript React.js / Angular / Vue.js Experience with back-end technologies : Node.js / Java / Python / PHP Express.js / Spring Boot / Django (any one) Hands-on experience with databases : MySQL / PostgreSQL / MongoDB Understanding of REST APIs , JSON, and web services Familiarity with Git, GitHub, and version control workflows Basic knowledge of cloud platforms (AWS / Azure / GCP) is a plus Understanding of Agile / Scrum methodologies Strong problem-solving, analytical, and communication skills Ability to work independently and in a team environment
Role & responsibilities Collect, clean, and preprocess datasets for analysis Perform exploratory data analysis (EDA) to uncover trends and patterns Assist in building dashboards and reports using tools like Excel, Google Sheets, Power BI, or Tableau Support the team by preparing data visualizations and presentations Work with analytics leads to identify business insights and recommendations Document findings, workflows, and analysis results clearly Collaborate with cross-functional teams on ongoing data-related projects Stay updated with current analytics tools, techniques, and best practices