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Bosscoder School of Technology

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Data Engineering

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Rajat Garg

The program is designed for software engineers, developers, data professionals, and working professionals who want to transition into AI, Machine Learning, or Generative AI roles. Basic Python knowledge is recommended, but prior Machine Learning experience is not required.

Who should join the Bosscoder Academy GenAI & ML Engineer Program?

The Bosscoder Academy GenAI & ML Engineer program follows a 9-month learning journey consisting of 8 structured modules covering Machine Learning, Deep Learning, Generative AI, Agentic AI, MLOps, and career preparation.

How long is the Bosscoder Academy GenAI & ML Engineer Program?

The program includes resume reviews, LinkedIn optimization, application guidance, referrals through the Bosscoder network, interview preparation, and access to 400+ hiring partnerships with technology companies.

What kind of placement support is available?

Depending on your background and experience, the curriculum prepares learners for roles such as AI/ML Engineer, Generative AI Engineer, LLM Engineer, Data Scientist, and MLOps/AI Platform Engineer.

What career roles can this program prepare me for?

Explore the Bosscoder Academy GenAI & ML Engineer Program curriculum, 1:1 mentorship, projects, placement support, and career outcomes.

Bosscoder Academy GenAI & ML Engineer Program Guide

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Bosscoder Academy GenAI & ML Engineer Program: Curriculum, Mentorship & Placement Support

The Bosscoder Academy Applied GenAI Program is suitable for software engineers, working professionals, product managers, career switchers, fresh graduates, and anyone who wants to build practical Generative AI skills. Basic Python knowledge is helpful, but prior AI or Machine Learning experience is not required.

Who should join the Bosscoder Academy Applied GenAI Program?

No. The curriculum starts with AI fundamentals, Python, and Prompt Engineering before progressing to advanced topics like RAG, LLM Fine-Tuning, Agentic AI, and LLMOps.

Do I need prior experience in AI or Machine Learning?

This program includes hands-on experience with tools such as OpenAI API, Anthropic, LangChain, LangGraph, CrewAI, Pinecone, ChromaDB, Hugging Face, FastAPI, Docker, AWS, LangSmith, DeepEval, PromptFoo, and other technologies used in production AI development.

What tools and technologies will I learn in this program?

Yes. You'll work on 10+ portfolio-ready projects, including RAG applications, AI agents, fine-tuned language models, AI chatbots, evaluation systems, and a production-ready capstone project that demonstrates your practical skills.

Will I build real-world AI projects?

The curriculum is designed to help learners build skills relevant to roles such as GenAI Engineer, LLM Engineer, AI Product Developer, Agentic AI Developer, and Technical Product Manager (AI).

What career roles can this bosscoder program prepare me for?

Unlike many courses that focus only on prompt engineering or basic AI concepts, this Bosscoder Applied GenAI Program covers the complete GenAI development lifecycle from Prompt Engineering and RAG to LLM Fine-Tuning, Agentic AI, LLMOps, deployment, AI safety, and production-ready projects.

How is this bosscoder program different from other GenAI courses?

Explore the Bosscoder Academy Applied GenAI Program curriculum, hands-on AI projects, career outcomes, placement support, and GenAI tools.

Bosscoder Academy Applied GenAI Program: Curriculum & Career

Bosscoder Academy Applied GenAI Program: Curriculum, Mentorship, Career Outcomes & Placement Support

Discover how Kapil strengthened DSA and system design skills with Bosscoder Academy and grew confidently as a software engineer at Disney.

Bosscoder Academy Review: Kapil's Journey to Disney

Bosscoder Academy Review: How Kapil Mastered DSA & System Design and Reached Disney

Read how Sourabh switched from Samsung to Microsoft with structured preparation, 1:1 mentorship, and guidance from Bosscoder Academy.

Bosscoder Academy Review: Samsung to Microsoft Journey

Bosscoder Academy Review: How Sourabh Switched from Samsung to Microsoft as a Software Engineer

These include programming (Python and SQL), cloud-service providers (AWS and Azure), big data systems (Hadoop and Spark), and database.

What skills are needed to become a Data Engineer?

It may take about 1–2 years to obtain the main set of skills, with further daily training and work experience.

How long does it take to become a Data Engineer?

Obtaining certification such as AWS Certified Solutions Architect or Google Professional Data Engineer can make a difference in your profile.

Which certifications are helpful for becoming a Data Engineer?

Kickstart your journey with the data engineering roadmap 2026. This ultimate guide offers the skills need to excel in data engineering.

Data Engineering Roadmap 2026

Data Engineering Roadmap 2026: Become a Data Engineer

To get started, pick a relevant problem to solve, gather a relevant dataset, and build and test models using Scikit-learn or TensorFlow (or a similar tool) as a beginner.

How do I get started with a machine learning project?

Learning basic Blockchain can take some time at first, but with some structured learning resources, practice, and some patience, beginners can learn the basics of it and get to working on some practical project.

Is learning machine learning difficult for beginners?

You sure can try your hand at machine learning without even learning the basics of coding—there are no-code platforms like Google AutoML, KNIME, and Teachable Machine to name a few. But learning to code provides more opportunities.

Can you learn machine learning without knowing the programming?

Yes, students can begin by using free datasets, such as Kaggle, Colab, and open source libraries to learn by doing and start building a portfolio.

Can I work on machine learning projects as a student?

Other than the well known ones such as House Price Prediction or Spam Detection, you can take a look at projects such as Sentiment Analysis, Image Classification, or Weather Prediction to train your skills.

What are other beginner-friendly projects in machine learning?

Explore best machine learning projects for beginners & experts. Build real-world AI skills with easy, practical project ideas.

Best 15 Machine Learning Projects for Beginners (2026)

Best 15 Machine Learning Projects for Beginners to Advanced

The programs offered at Bosscoder will help you become job-ready by providing structured upskilling, including Data Structures & Algorithms (DSA), System Design, Mock Interviews, Resume Building, and 1:1 Mentorship, in order to allow working professionals to increase their interview readiness prior to applying for jobs at product-based companies.

How do Bosscoder programs help software engineers become job-ready?

Yes, the programs provided by Bosscoder are specifically designed for working professionals who want to strengthen their fundamentals and develop problem-solving skills, as well as for those looking to make a job switch while working full-time.

Is Bosscoder Academy suitable for working professionals with 2-5 years of experience?

Most product-based companies evaluate candidates based on their Data Structures & Algorithms (DSA), system design capabilities, problem-solving abilities, communication skills, and a well-structured resume that highlights measurable impact.

What skills are required to become job-ready for product-based companies?

Bosscoder Academy provides structured learning, mock interviews, resume reviews, LinkedIn optimization, 1:1 mentorship, and placement support to help preparing professionals with technical interviews and opportunities for advancement in their careers.

Can Bosscoder Academy help with job switches and interview preparation?

Learn how Bosscoder programs help working professionals become job-ready with DSA, system design, 1:1 mentorship, and interview preparation.

How Bosscoder Programs Make You Job-Ready for Top Tech Roles

How Bosscoder Academy Helps Working Professionals Become Job-Ready for Product-Based Companies

Yes, Bosscoder Academy has developed its Data Engineering program with working professionals in mind and includes structured learning path, 1:1 mentorship, hands-on experience with actual projects, help getting through an interview, and career support help, all while being able to work full-time.

Is Bosscoder Academy's Data Engineering Program suitable for working professionals?

Bosscoder Academy's Data Engineering curriculum covers all of the following topics: SQL, Python, Data Warehousing, ETL Pipelines, Apache Spark, Kafka, Cloud Computing Technology, System Design, Big Data Processing, and the latest AI/ML concepts. The content also follows a step-by-step guide that matches the requirements needed by companies.

What topics are covered in Bosscoder Academy's Data Engineering curriculum?

Unlike self-study methods, the structure of Bosscoder Academy allows learners to have access to a complete guide through their journey, get assistance from their instructor, gain practical project experience, practice with mock interviews, receive help writing an effective resume, get help optimizing their LinkedIn account, and get placed in a Data Engineering position therefore, learners can be accountable for their progress and stay focused on their career goals.

How is Bosscoder Academy different from self-learning Data Engineering?

The program includes career-focused services such as interview preparation, mock interviews, resume building, LinkedIn optimization, and placement assistance. Combined with practical projects and 1:1 mentorship, it helps professionals prepare for Data Engineering opportunities and long-term career growth.

Does Bosscoder Academy's Data Engineering Program help with job switches and career growth?

Explore Bosscoder Academy's Data Engineering Program curriculum, mentorship, projects, and career support for working professionals.

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