AI Engineer Pro — From Python to Agentic AI Course in Bangalore
Become a job-ready AI Engineer in this complete 210-hour career programme — no prior coding experience required. Master Python, Machine Learning, Deep Learning, MLOps, and Agentic AI through three hands-on capstone projects, then present your work at our employer demo day. Go from your first line of code to a portfolio of deployed AI systems, in an intimate 15-seat cohort with 1:1 mentorship.
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Key Features of AI Engineer Pro Course
- Complete Path — Python to Agentic AI
- ArivuSkills Certification
- Employer Demo Day
- Placement Assistance
- Real Capstone Projects
- Production-Ready Deployment Skills
- Hands-On, Project-Based Learning
- Live Mentor Access Throughout
Listen to your Success Stories
Why Choose ArivuSkills?
Employer Demo Day
Present your Industry capstone to invited employers from ArivuSkills’ B2B and corporate network — turning your final project into a direct hiring opportunity.
Placement Support
Interview preparation and support for your first 10 confirmed interviews, backed by a portfolio of three deployed projects.
Mock Interviews for AI Roles
Practice structured mock interviews modeled on real AI/Data Science hiring processes.
Arivu Skills Certification
Earn a certification from Arivu Skills recognizing hands-on, job-ready AI and Data Science skills.
Practitioner-Led Training
Learn directly from faculty with real experience building and deploying AI systems in industry.
Real Capstone Projects
Design, build, and present three end-to-end projects — Machine Learning, Deep Learning, and an Industry capstone.
Complete Foundation-to-Advanced Curriculum
No prior coding experience needed — go from Python fundamentals all the way to Agentic AI in one structured programme, nothing skipped.
Industry-Relevant Curriculum
Curriculum built around real market demand — ML, deep learning, MLOps, generative AI, and agents, not outdated theory.
Real Industry Case Studies
Work through practical datasets and problems throughout, just like production environments.
Small-Batch Learning
Cohort size scales with admissions each batch — real mentorship and individual feedback, not lost in a 100+ student batch.
Campus + Local Placement Network
Train at Arivu Skills’ physical campus with access to a genuine local employer network.
Career Guidance & Roadmap
A structured path from Python fundamentals to production AI systems to interview readiness, tailored to your background.
No Prior Experience Required
Open to freshers and career switchers — the only real requirement is basic computer literacy, not a coding background.
Weekend-Friendly Format
210 hours delivered over 6 months of weekend batches, with campus, live, and recorded access combined.
Who Can Join this Course?
- Recent graduates from any academic background — no coding experience required
- Freshers looking to build a career in AI, Data Science, or Machine Learning
- Career switchers from non-tech fields wanting a structured path into AI
- Students who want a complete portfolio and demo-day proof before job hunting
- Anyone wanting to go from Python fundamentals all the way to Agentic AI in one programme
- Candidates who prefer weekend/hybrid learning over quitting a job or degree
- Those who want real mentorship in a small cohort, not a 100+ seat online batch
- Professionals already confident in Python who want to skip straight to advanced AI content
Significant Demand Growth Since 2022
The demand for AI professionals is accelerating fast in India, and freshers are entering the market at a genuinely strong starting point. AI/ML fresher hiring grew sharply in 2026, and candidates with real, deployed project experience are earning well above the market average from day one. India needs at least 1 million skilled AI professionals by 2026, and companies are actively hiring freshers who can prove hands-on capability — not just course completion. Enter this high-demand field with the AI Engineer Pro course from ArivuSkills.
Testimonials
Rajiv Singh
Nitish Sharma
Dimple Prasad
Let's walk you through the journey at ArivuSkills
Course Curriculum
Our course is designed by industry experts for excellent academic and industrial experience. We have a balanced combination of theoretical, technical, and practical knowledge for you to get the best training experience for everyone regardless of their background.
- 6 Months
Python Fundamentals
→ Module 1: Python Fundamentals
– Setup, variables, data types, casting, I/O, operators
– Control flow, loops, functions, *args/**kwargs, lambda, scope
– Lists, tuples, sets, dictionaries & comprehensions; OOP (classes, inheritance, polymorphism)
– File I/O; exceptions; modules
NumPy & Pandas
→ Module 2: NumPy & Pandas
– ndarray, indexing, broadcasting, vectorisation, linear algebra
– Pandas Series/DataFrame, loc/iloc, filtering, apply/map
– Advanced Pandas: groupby, merge/join, pivot, missing data, datetime
Statistics & Probability
→ Module 3: Statistics & Probability
– Descriptive stats, probability, Bayes, distributions
– Inferential stats, CLT, confidence intervals, hypothesis tests, ANOVA, correlation
Data Visualization
→ Module 4: Data Visualization
– Matplotlib & Seaborn mastery
→ Module 5: SQL
– SELECT, JOINs, GROUP BY, subqueries, CTEs, window functions
End-to-End EDA Project
→ Module 6: End-to-End EDA Project
– Full exploratory data analysis project with data cleaning
Intro to Machine Learning
→ Module 7: Intro to Machine Learning
– ML landscape & types; linear/multiple regression
– Gradient descent; R²; polynomial; Ridge/Lasso; cross-validation
Classification
→ Module 8: Classification
– Logistic regression, KNN
– Confusion matrix, precision/recall/F1, ROC-AUC
– Decision trees; Naive Bayes
Ensemble Methods
→ Module 9: Ensemble Methods
– Bagging; Random Forest; tuning; OOB
– Boosting — AdaBoost, XGBoost, LightGBM, CatBoost; GridSearch/Optuna
Unsupervised Learning
→ Module 10: Unsupervised Learning
– K-Means, hierarchical, DBSCAN, GMM; cluster evaluation
– PCA, t-SNE, UMAP, LDA
Feature Engineering
→ Module 11: Feature Engineering
– Scaling, encoding, feature selection, imbalanced data (SMOTE)
– Scikit-learn Pipelines, ColumnTransformer, stacking
Capstone 1 (Machine Learning)
→ Module 12: Capstone 1 (Machine Learning)
– Problem definition, EDA, feature engineering, baseline, tuning
– SHAP/LIME, presentation
Deep Learning Foundations
→ Module 13: Deep Learning Foundations
– Neurons, activations, forward/back-prop, loss functions
– TensorFlow/Keras API, optimisers, dropout
– PyTorch tensors, autograd, training loop, GPU
CNNs & Computer Vision
→ Module 14: CNNs & Computer Vision
– CNNs — convolution, pooling, VGG/ResNet, transfer learning
– Advanced CV: object detection (YOLO), segmentation
NLP & Sequence Models
→ Module 15: NLP & Sequence Models
– NLP — tokenization, TF-IDF, Word2Vec, sentiment analysis
– RNN, LSTM, GRU, seq2seq, attention
Transformers
→ Module 16: Transformers
– Self-attention, BERT, HuggingFace
Time Series & Recommender Systems
→ Module 17: Time Series & Recommender Systems
– Stationarity, ARIMA/SARIMA, Prophet; LSTM for sequences
– Recommender systems, collaborative filtering
Capstone 2 (Deep Learning)
→ Module 18: Capstone 2 (Deep Learning)
– CV/NLP/Time-Series project; architecture, training, tuning
– Evaluation, optimisation, documentation, presentation
MLOps
→ Module 19: MLOps
– MLflow tracking & model registry; Weights & Biases
– Docker, Dockerfile, Compose, registries
Deployment
→ Module 20: Deployment
– REST APIs; Flask & FastAPI; serialisation
– Cloud (AWS/GCP); Streamlit/Gradio; CI/CD; drift
Data Engineering
→ Module 21: Data Engineering
– ETL/ELT; Airflow; PySpark; warehousing
– SQL vs NoSQL; MongoDB; vector databases; cloud storage; DVC
Generative AI & LLMs
→ Module 22: Generative AI & LLMs
– LLM evolution; OpenAI and Anthropic APIs; prompting
– ReAct/ToT; function calling; fine-tuning (LoRA); Ollama
RAG & LangChain
→ Module 23: RAG & LangChain
– RAG pipelines, chunking, embeddings, vector stores
– LangChain chains, memory, tools, LCEL; LangSmith
AI Agents
→ Module 24: AI Agents
– Agent architecture, ReAct, tool use
– LangGraph, CrewAI, AutoGen; multi-agent; guardrails; deployment
Capstone 3 (Industry)
→ Module 25: Capstone 3 (Industry)
– End-to-end AI system: pipeline + model + agent
– Architecture, build, integration, testing; demo-day prep
Demo Day & Placement
→ Module 26: Demo Day & Placement
– Employer demo day; GitHub portfolio; resume; LinkedIn
– Mock interviews; graduation & co-certification
Career Track
Once you have enrolled for the program then you will have access to a wide range of resources which will help you in becoming a Job-Ready Candidate. We have a dedicated placement team of professionals who excel in their individual domains committed to assist you in our journey.
- 1 Months
Portfolio & Capstone Documentation
- Document all three capstones — Machine Learning, Deep Learning, and Industry — as GitHub portfolio projects
- Showcase your end-to-end AI system build from Capstone 3, including pipeline, model, and agent integration
- Write up your problem framing, approach, and key design decisions for each project
- Present your work in a way employers can evaluate directly
Resume & LinkedIn for AI Roles
- Build a resume highlighting your Python-to-Agentic-AI journey and three deployed projects
- Optimize your LinkedIn profile for AI Engineer, Data Scientist, and ML Engineer roles
- Learn how to translate coursework into role-relevant achievements for freshers with no prior work experience
Mock Interviews for AI Roles
- Practice structured mock interviews covering ML fundamentals, coding rounds, and case-study style questions
- Get feedback on technical communication and problem-solving under real interview conditions
- Prepare for entry-level AI/Data Science interview formats specifically, not generic software interviews
Mock FDE Interviews
- Present your Capstone 3 (Industry) project to invited employers from ArivuSkills’ B2B and corporate network
- Turn your final project into a direct hiring conversation
- Receive interview preparation and support for your first 10 confirmed interviews, backed by your full portfolio
Get Placed
Companies Hiring for AI Engineer Professionals
80%
Placements
8 LPA
Average CTC
25 LPA
300+
35%
AI Engineer Pro Course Training in Bangalore
- Batches Forming Soon
Applications open — Batch dates announced soon
IST: 09:00 AM – 01:00 PM
- Weekend Batch | 120 Sessions
- Certified Trainer
Do you want to customize your batch request?
Corporate Training
The work force is your asset. Up-Skill them with our Corporate Training Programs!
- Unleash In-Demand Skills Across the Enterprise
- Align Skill Development with Business Objectives
- Drive Increased Employee Productivity
- Leverage Immersive Learning
AI Engineer Pro Certification Course in Bangalore Overview
How AI Engineer Pro Certification Impacts Your Career
An ArivuSkills Certification from this course opens strong career opportunities in Machine Learning, Data Science, and AI Engineering roles — even for candidates starting with zero coding background.
Career Advancement:
- Strong Demand: AI and Machine Learning represent one of the fastest-growing hiring categories in India’s tech market in 2026, with fresher hiring in AI/ML growing sharply year-on-year. Candidates with real, deployed project experience are earning meaningfully above the market average, especially in:
- AI Engineer
- Machine Learning Engineer
- Data Scientist
- AI/ML Developer
- Strong Career Demand: AI Engineering skills are highly valued across:
- IT-Services Firms
- Product Companies & GCCs
- AI-native Startups
- Enterprise Data & Analytics Teams
- E-commerce, Fintech & BFSI
Note: this is a complete foundation-to-advanced program built for freshers and career switchers — no prior coding experience required.
What’s Included in the Course?
The AI Engineer Pro Program by ArivuSkills provides practitioner-led, job-oriented training taking you from Python fundamentals to production-ready Agentic AI systems.
✔ Python, Statistics & Data Analysis Foundations
✔ Machine Learning & Ensemble Methods
✔ Deep Learning, Computer Vision & NLP
✔ MLOps, Deployment & Data Engineering
✔ Generative AI, RAG & LangChain
✔ AI Agents (LangGraph, CrewAI, AutoGen)
✔ 3 Real Capstone Projects — ML, Deep Learning & Industry
✔ Employer Demo Day, Portfolio & Placement Support
✔ 6-Month Weekend Access (Campus + Live + Recorded)
Eligibility & Requirements
Who Can Join?
- Recent Graduates & Freshers from Any Academic Background
- Career Switchers Looking to Enter AI, Data Science, or ML
- Candidates with Basic Computer Literacy — No Prior Coding Required
AI Engineer Pro Course Certificate
Skills Covered
- Python, Statistics & Data Analysis
- Machine Learning & Ensemble Methods
- Deep Learning, CV & NLP
- MLOps & Production Deployment
- Generative AI, RAG & LangChain
- AI Agents & Multi-Agent Systems
Tools Covered
AI Engineer Pro Certification Course in Bangalore FAQ
1. What is AI Engineer Pro and who is it for?
AI Engineer Pro is a complete 210-hour career programme covering Python, Machine Learning, Deep Learning, MLOps, and Agentic AI. It’s designed for freshers, recent graduates, and career switchers — no prior coding experience is required.
2. Do I need any coding background to join this course?
No. The programme starts from Python fundamentals and builds up to advanced AI systems, so you can join with zero coding experience. The only requirement is basic computer literacy.
3. What's the difference between AI Engineer Pro and Generative & Agentic AI Specialist?
AI Engineer Pro is the complete foundation-to-advanced track (210 hours, 6 months) for freshers with no prior Python knowledge. Generative & Agentic AI Specialist is a focused, advanced 100-hour course (3 months) for professionals who already know Python and want to go deep into LLMs and agentic AI without repeating the basics.
4. How is the course delivered?
Weekend batches combining live sessions, recorded content, and campus access in Bangalore, Chennai, and Coimbatore.
5. What is the batch size and teaching format?
Small-batch cohorts with real mentorship and individual feedback, delivered through hands-on, project-based learning rather than passive lectures.
6. What if I fall behind during the programme?
Recorded sessions are available for every module, so you can revisit any topic at your own pace alongside the live weekend schedule.
7. What certification will I receive?
An ArivuSkills Certification recognizing hands-on, job-ready AI and Data Science skills, based on your three capstone projects and course completion.
8. What projects will I build during the course?
Three real capstone projects — a Machine Learning project, a Deep Learning project (Computer Vision, NLP, or Time Series), and a final Industry capstone combining a data pipeline, model, and AI agent into one deployed system.
9. Does the course cover Generative AI and AI Agents too?
Yes. Beyond the full ML and Deep Learning foundation, the programme includes dedicated modules on LLMs, RAG, LangChain, and multi-agent frameworks (LangGraph, CrewAI, AutoGen) in the final phase.
10. What kind of placement support is included?
Interview preparation and support for your first 10 confirmed interviews, backed by a portfolio of three deployed projects, resume and LinkedIn support, mock interviews, and a spot at our employer demo day.
Distinctions and Achievements
Explore the milestones of our journey!
Best Skill Learning Institute of the Year
The Education Excellence Award by Brands Impact
Edutech Company of the Year
The Education Awards by The Corporate Titan
Institute with the Best Placement
The Education Awards by Mantra
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