The AI Engineer Course 2025: Complete AI Engineer Bootcamp
Complete AI Engineer Training: Python, NLP, Transformers, LLMs, LangChain, Hugging Face, APIs

4.5 Stars

Duration: Choose Your Course Length —
1, 2, 3, 4, 5, or 6 Months (Online & Remote)
📌 BATCH START DATE:
⏰ LAST DATE TO APPLY:
⏳ Batch Starts In:
₹3999/- ₹1999/- 🎯
📢 Enroll Now & Save Big!
REGISTRATION FORM
Fill up the Below form to get registered in the program
OUR STUDENTS ARE SELECTED IN

About This Course
Artificial Intelligence with Machine Learning is transforming industries by enabling systems to learn from data, adapt, and make intelligent decisions. This course is designed to give you practical, hands-on skills in developing AI-powered solutions using Machine Learning algorithms, Python, TensorFlow, Scikit-learn, and real-world datasets.
Whether you’re a student, aspiring data scientist, or working professional, this course will help you build, train, and deploy ML models that solve real-world problems across various domains like healthcare, finance, marketing, and more.
✅ No prior AI/ML experience required. We start from the fundamentals and guide you step-by-step into advanced concepts, ensuring you can confidently work on industry-grade projects.
What You Will Learn
- The course provides the entire toolbox you need to become an AI Engineer
- Understand key Artificial Intelligence concepts and build a solid foundation
- Start coding in Python and learn how to use it for NLP and AI
- Impress interviewers by showing an understanding of the AI field
- Apply your skills to real-life business cases
- Harness the power of Large Language Models
- Leverage LangChain for seamless development of AI-driven applications by chaining interoperable components
- Become familiar with Hugging Face and the AI tools it offers
- Use APIs and connect to powerful foundation models
- Utilize Transformers for advanced speech-to-text
Foundations of AI & Machine Learning
What is Machine Learning and how it differs from traditional programming
Real-world applications across industries (finance, healthcare, retail, automation, etc.)
Understanding supervised, unsupervised, and reinforcement learning
Data Processing & Feature Engineering
Basics of data collection, cleaning, and preprocessing
Feature selection and dimensionality reduction techniques
Handling missing data and preparing datasets for ML models
Core Machine Learning Algorithms
Regression, classification, and clustering algorithms
Decision trees, random forests, and ensemble learning
Model evaluation and performance metrics
Deep Learning & Neural Networks
Basics of deep learning and how neural networks work
Using TensorFlow and PyTorch for building models
CNNs for image recognition, RNNs for sequence data
Model Deployment & Real-World Projects
How to deploy ML models using APIs and cloud platforms
Automating workflows with ML pipelines
Real-world projects like sales forecasting, fraud detection, and sentiment analysis
Career & Practical Readiness
Using AI/ML skills in freelancing and job workflows
Resume building with ML projects
Exploring AI/ML career paths in corporate and startup environments
Course content
76 sections – 429 lectures – 28h 14m total length
Building an AI tool in 5 minutes: A quick demo – 10:16 (Preview)
What does the course cover – 03:17 (Preview)
Natural vs Artificial Intelligence – 02:06 (Preview)
Brief history of AI – 00:41
Demystifying AI, Data science, Machine learning, and Deep learning – 02:27
Weak vs Strong AI – 02:43
Quiz 1 – 4 questions
Structured vs Unstructured data – 01:47 (Preview)
How we collect data – 04:02
Labelled and unlabelled data – 02:06
Metadata: Data that describes data – 01:42
Quiz 2 – 3 questions
Machine learning – 06:15
Supervised, Unsupervised, and Reinforcement learning – 05:34
Deep learning – 08:27
Quiz 3 – 3 questions
Robotics – 04:35
Computer vision – 04:14
Traditional ML – 04:05
Generative AI – 02:16
Quiz 4 – 3 questions
The rise of Gen AI: Introducing ChatGPT – 02:09
Early approaches to Natural Language Processing (NLP) – 02:42
Recent NLP advancements – 03:01
From Language Models to Large Language Models (LLMs) – 06:11
The efficiency of LLM training. Supervised vs Semi-supervised learning – 03:22
From N-Grams to RNNs to Transformers: The Evolution of NLP – 05:22
Phases in building LLMs – 06:40
Prompt engineering vs Fine-tuning vs RAG: Techniques for AI optimization – 04:24
The importance of foundation models – 02:49
Buy vs Make: Foundation models vs Private models – 02:36
Inconsistency and hallucination – 02:43
Budgeting and API costs – 02:58
Latency – 01:46
Running out of data – 02:25
Python programming – 02:07
Working with APIs – 01:35
Vector databases – 03:11
The importance of open source – 01:31
Hugging Face – 01:46
LangChain – 02:54
AI evaluation tools – 03:07
AI strategist – 05:08
AI developer – 04:27
AI engineer – 03:53
🕒 2 lectures – 5 mins
AI ethics – 01:56
Future of AI – 03:03
Programming explained in a few minutes – 05:29
Why Python – 04:32
This course includes:
- 28 hours on-demand video
- 98 coding exercises
- 17 articles
- 137 downloadable resources
- Certificate of completion
About The Instructor
Instructor: Arjun Mehta
AI & Machine Learning Specialist | Industry Expert | Educator
Arjun Mehta is an accomplished AI and Machine Learning educator with over 7 years of experience in building intelligent applications, predictive models, and data-driven solutions. He has worked on real-world AI projects across sectors such as fintech, healthcare, and e-commerce, delivering impactful and scalable solutions.
Having collaborated with top Indian IT companies and global clients, Arjun brings a blend of academic insight and industry expertise into his teaching. At Skillsecure X , he leads curriculum design and provides mentorship for AI, ML, and Deep Learning programs.
Major Project:
Major Project: AI-Powered Movie Recommendation System
Objective:
Build a machine learning-based recommendation engine that suggests movies to users based on their viewing history, ratings, and preferences.
Description:
Students will create an intelligent movie recommendation system using Python, Pandas, and Scikit-learn. The project will cover data preprocessing, feature engineering, model selection, training, and evaluation. Learners will work with a real-world dataset (such as the MovieLens dataset) and implement collaborative filtering and content-based recommendation techniques.
Key Skills You Will Learn:
Data cleaning and preprocessing
Exploratory data analysis (EDA)
Feature engineering
Machine learning model building (KNN, cosine similarity, or matrix factorization)
Model evaluation (precision, recall, RMSE)
Deploying a simple web-based interface using Streamlit or Flask
Outcome:
By the end of this project, you will have a fully functional AI application that can recommend movies just like Netflix, Amazon Prime, or Disney+, and you’ll understand how recommendation systems work in the real world.









Trusted Collaborators













Description
The Problem
AI Engineers are best suited to thrive in the age of AI. It helps businesses utilize Generative AI by building AI-driven applications on top of their existing websites, apps, and databases. Therefore, it’s no surprise that the demand for AI Engineers has been surging in the job marketplace.
Supply, however, has been minimal, and acquiring the skills necessary to be hired as an AI Engineer can be challenging.
So, how is this achievable?
Universities have been slow to create specialized programs focused on practical AI Engineering skills. The few attempts that exist tend to be costly and time-consuming.
Most online courses offer ChatGPT hacks and isolated technical skills, yet integrating these skills remains challenging.
The Solution
AI Engineering is a multidisciplinary field covering:
AI principles and practical applications
Python programming
Natural Language Processing in Python
Large Language Models and Transformers
Developing apps with orchestration tools like LangChain
Vector databases using PineCone
Creating AI-driven applications
Each topic builds on the previous one, and skipping steps can lead to confusion. For instance, applying large language models requires familiarity with Langchain—just as studying natural language processing can be overwhelming without basic Python coding skills.
So, we created the AI Engineer Bootcamp 2024 to provide the most effective, time-efficient, and structured AI engineering training available online.
This pioneering training program overcomes the most significant barrier to entering the AI Engineering field by consolidating all essential resources in one place.
Our course is designed to teach interconnected topics seamlessly—providing all you need to become an AI Engineer at a significantly lower cost and time investment than traditional programs.
The Skills
1. Intro to Artificial Intelligence
Structured and unstructured data, supervised and unsupervised machine learning, Generative AI, and foundational models—these familiar AI buzzwords; what exactly do they mean?
Why study AI? Gain deep insights into the field through a guided exploration that covers AI fundamentals, the significance of quality data, essential techniques, Generative AI, and the development of advanced models like GPT, Llama, Gemini, and Claude.
2. Python Programming
Mastering Python programming is essential to becoming a skilled AI developer—no-code tools are insufficient.
Python is a modern, general-purpose programming language suited for creating web applications, computer games, and data science tasks. Its extensive library ecosystem makes it ideal for developing AI models.
Why study Python programming?
Python programming will become your essential tool for communicating with AI models and integrating their capabilities into your products.
3. Intro to NLP in Python
Explore Natural Language Processing (NLP) and learn techniques that empower computers to comprehend, generate, and categorize human language.
Why study NLP?
NLP forms the basis of cutting-edge Generative AI models. This program equips you with essential skills to develop AI systems that meaningfully interact with human language.
4. Introduction to Large Language Models
This program section enhances your natural language processing skills by teaching you to utilize the powerful capabilities of Large Language Models (LLMs). Learn critical tools like Transformers Architecture, GPT, Langchain, HuggingFace, BERT, and XLNet.
Why study LLMs?
This module is your gateway to understanding how large language models work and how they can be applied to solve complex language-related tasks that require deep contextual understanding.
Requirements
- No prior experience is required. We will start from the very basics
- You’ll need to install Anaconda. We will show you how to do that step by step
Who this course is for:
- You should take this course if you want to become an AI Engineer or if you want to learn about the field
- This course is for you if you want a great career
- The course is also ideal for beginners, as it starts from the fundamentals and gradually builds up your skills
"Get Industry level Certification!"

4.5 Stars

Duration: Choose Your Course Length —
1, 2, 3, 4, 5, or 6 Months (Online & Remote)
📌 BATCH START DATE:
⏰ LAST DATE TO APPLY:
⏳ Batch Starts In:
₹3999/- ₹1999/- 🎯
📢 Enroll Now & Save Big!
REGISTRATION FORM
Fill up the Below form to get registered in the program
Meet our Ex-Interns
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FAQs
To begin, complete the registration form above by entering your name, email ID, and mobile number. Mention if you’re a student or a professional, along with your college or workplace details. You can also pick a convenient start date, and we’ll try our best to match it.
📩 Offer Letter: After we verify your registration, your offer letter will be issued and sent to your email within a few hours or the next morning.
📩 Welcome Package: On your chosen start date, you’ll receive login credentials and step-by-step guidance via email.
In case you have any queries, you can reach out through hr@skillsecurex.com or WhatsApp/call +91-7618025090.
Definitely! Our support team assists with college-required documents such as attendance sheets, evaluation reports, progress updates, and project summaries throughout your program.
If you need to take a leave for any reason, simply email us or drop a WhatsApp message. You don’t have to wait for a response — just inform us and focus on your priority. Once you’re ready, you can easily resume your tasks.
Yes, a laptop or desktop with a good internet connection is mandatory for participating in this program.
Our programs feature pre-recorded video sessions and LIVE sessions both (Hybrid ) to offer maximum flexibility. Everyone — students, professionals, and mentors — can learn at their own pace without schedule conflicts.
Don’t worry there is an AI-powered assistant to help you with all your coding-related queries. Andie can check and debug code, generate new code, and even build entire projects for you.
This feature is exclusively available to registered candidates through their Task Portal.
Since mentors cannot be available 24/7, Andie was developed to bridge the gap. Located at the bottom-left corner of every module, this Full Stack Developer Bot is capable of writing, reviewing, and troubleshooting code anytime, ensuring you get instant solutions to your coding challenges, day or night.
This internship cum training opportunity is designed in such a way as from fresher to a professional anyone can get benefit out of it, The opportunity is divided into 15+ modules, and every Module contains 15-20 small tasks plus 1 project (in the last) based upon what you have learnt in that particular module. The complexity and practicality of your modules and projects will gradually increase, Timing is flexible, schedule yours accordingly. After completing every project given in the modules, Submit within the deadlines.
A major part of this program contains a training part, however we have many projects (2 Major, 15 Minor and many practice projects) and many internal and external resources to sharpen the skills of the candidates. It is a self paced program, Training and internships will go simultaneously. After every Module, there will be a project related to it (may it be a minor, major or practice project)
We have 20+ projects to provide hands on Experience and sharpen the skills of the Interns.
About Paid Projects_
Paid projects will be provided to the interns on two basis
1) The assignments/projects, which all students sends goes directly to our USA team. they evaluate all of them and create a kind of ranking sheet based upon some factors like quality, accuracy, deadline met etc. They keep this list with them for future paid projects.
2) The availability and number of the projects available.
The training is split into 15+ modules, each with 15–20 tasks and one project. As you progress, the complexity grows to ensure steady skill development. Projects must be submitted on time, and you can plan your schedule flexibly.
You’ll work on over 20 projects to build real-world experience.
👉 Paid Project Opportunity: Based on your performance (quality, speed, and accuracy), you may be eligible for paid tasks offered by our USA team, subject to availability.
Anyone interested can join! Basic knowledge of HTML, CSS, or JavaScript is a bonus but not compulsory. Graduates from any stream are welcome. There are no restrictions based on nationality, age, or background.
You decide your working hours! Whether you’re a student or a working professional, you can complete modules at your convenience. Plus, the internship is 100% remote — work from wherever you are most comfortable.
Once enrolled, you’ll have lifetime access to all training content, unless there’s a policy change in the future.
Absolutely! You’ll receive full training material, video tutorials, and 24/7 coding assistance before and during your project work.
Yes, but it depends! Stipends are offered based on your performance, the nature of the project, and USA team evaluations. Stipends typically range from ₹8,000 to ₹18,000 INR ($99 – $219) or higher, depending on project availability.
We actively hire top-performing interns for internal and client roles based on project availability. Additionally, we regularly post openings from our partners so you can apply even after completing the program.
Your certificate will be automatically prepared and scheduled to be emailed around your program completion date. Allow up to 48 extra hours if it falls on a weekend or holiday.
LORs are awarded to exceptional candidates based on strict performance criteria. If you require a LOR for special circumstances like studying abroad, you may also directly request it from HR.
Of course! Although not mandatory, if you find the program valuable, feel free to refer it to friends, classmates, or colleagues who might benefit.
4.5 Stars

SkillSecureX is a forward-thinking EdTech company dedicated to transforming how students and aspiring professionals build careers in the IT sector. Founded with a vision to make high-quality, industry-relevant learning accessible to all, SkillSecureX specializes in online internships and certified training programs in Web Development, Data Science, Artificial Intelligence, and other cutting-edge technologies.
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SkillSecureX Technologies
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- +91-7618025090
- +91-7618025090
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Student Support & Internship Queries:
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1128 International Parkway, Fredericksburg, VA 22406, United States
- hr@skillsecurex.com
Careers/Job Applications (US Office):
- careers.usa@skillsecurex.com
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- media@skillsecurex.com
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