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Home/ Courses/ Certifications/ Machine Learning Certification
🤖 Machine Learning Certification Course

Machine Learning Certification — Build Models That Learn From Data

Deep ML certification — algorithms, neural networks, NLP and deployment. Build 10 real-world ML models and earn an industry-recognized certificate.

💬 Enrol via WhatsApp 📄 Download Brochure
5 Months
Duration
10 Models
Built From Scratch
92%
Job Transition Rate
₹0
Donation Required
Enrolment Open
₹17,999
Course Fee
🤖
ML Certification
scikit-learn · TensorFlow · PyTorch · MLOps — comprehensive machine learning programme
TensorFlow
+ PyTorch
MLOps
Included
10
Projects
🏆 Industry Certified
✅ Job Assistance
Overview
Curriculum
Tools
Who Should Join
Careers
Certification
FAQs
What You'll Learn

From ML Fundamentals to Production-Ready Models

This ML certification takes you from statistical learning through deep neural networks, NLP and computer vision — then shows you how to deploy models at scale. Aligned with the skills Google, Amazon and ML-first companies test in interviews.

📐
ML Fundamentals
Bias-variance, loss functions, gradient descent — the math behind ML.
🌲
Supervised Learning
Linear models, SVMs, ensemble methods — core ML algorithms.
🧩
Unsupervised Learning
K-means, DBSCAN, PCA, autoencoders — pattern discovery.
🧠
Neural Networks
Backpropagation, CNNs, RNNs — deep learning foundations.
📝
NLP & Text Models
Transformers, BERT, GPT fine-tuning — modern language AI.
👁️
Computer Vision
Object detection, segmentation, YOLO, image classification.
⚙️
MLOps & Deployment
MLflow, Docker, Kubernetes, CI/CD for ML pipelines.
📊
ML in Production
A/B testing, model monitoring, data drift detection.
Curriculum

Module-by-Module Breakdown

Every module culminates in a working model you deploy and add to your GitHub portfolio.

1
Statistical ML Algorithms
4 weeks
RegressionClassificationSVMEnsemble MethodsCross-ValidationHyperparameter Tuning
2
Deep Learning
4 weeks
Neural NetworksBackpropagationCNNsRNNsLSTMsAttention Mechanism
3
NLP & Computer Vision
4 weeks
Text PreprocessingWord EmbeddingsTransformersBERTObject DetectionImage Segmentation
4
MLOps & Deployment
3 weeks
MLflowDockerFastAPIKubernetes BasicsModel MonitoringData Version Control
5
Capstone Projects
5 weeks
End-to-End ML PipelineNLP ChatbotVision Classification AppRecommendation SystemDeployment on AWS
Tools & Tech Stack

Industry Tools You'll Master

🤖scikit-learn
🔥PyTorch
🧠TensorFlow/Keras
🐍Python
📓Jupyter/Colab
🐳Docker
☁️AWS SageMaker
📊MLflow
🐙DVC
⚡Hugging Face
Who Should Join

This Course Is Built For

💻
Software Developers
Add ML skills to engineering background and move into ML engineering.
📊
Data Analysts
Upgrade from analytics to predictive modelling and ML.
🎓
CS/IT Graduates
Bridge the gap between theory and production ML systems.
🔬
Research Enthusiasts
Formalize ML skills and build a project portfolio for ML research roles.
Career Outcomes

ML Careers and Salaries

₹12–35L
Avg. ML Engineer Salary
92%
Job Transition Rate
300+
Hiring Partners
4–8 Mo
To ML Role
Top Hiring Companies
GoogleAmazonMicrosoftNvidiaSamsung R&DFlipkartSwiggyPhonePeRazorpayFractalTiger AnalyticsZS Associates
Roles & Salary Ranges
RoleAvg. Package (LPA)
ML Engineer (fresher)8–18
Senior ML Engineer (3 yr)18–40
AI Research Scientist20–50
MLOps Engineer15–30
Data Scientist + ML12–28
Certification

What You'll Earn

Vidyapaath Certified ML Engineer

Complete all 5 modules and deliver the capstone project to earn the Vidyapaath ML Engineering Certificate — verified on-chain, shareable on LinkedIn and recognized by 300+ hiring companies.

ML AlgorithmsDeep LearningNLP SpecialistComputer VisionMLOpsProduction ML
FAQs

Machine Learning Certification — Common Questions

What Python level do I need before starting?+
Intermediate Python — you should be comfortable writing functions, loops and using basic libraries (Pandas, NumPy). If not, our Data Science Certification includes a Python module that brings you to the required level first.
How is this different from the Data Science Certification?+
The Data Science cert covers the full data workflow (SQL, statistics, EDA, basic ML). This ML certification goes deeper — advanced algorithms, deep learning, NLP, computer vision and production deployment. Most students do Data Science first, then ML.
Are PyTorch and TensorFlow both covered?+
Yes — both frameworks are taught. Core neural network concepts are introduced in TensorFlow/Keras for ease, then the same implementations are shown in PyTorch. Job-ready students should know both.
Is there a capstone project requirement for the certificate?+
Yes — you must complete and submit a capstone ML project that is evaluated by our mentor panel. The project must demonstrate an end-to-end ML pipeline including deployment. This project is what most hiring companies actually evaluate in interviews.
What if I already know basic ML — can I skip modules?+
Yes — we offer a placement test. Students who demonstrate intermediate ML knowledge can skip to Module 3 (NLP & Vision) and complete only the advanced sections. Fee remains the same; contact us to arrange the assessment.
Does this course prepare for Google ML Engineer or AWS ML Specialty certifications?+
Yes — the curriculum aligns with the knowledge domains for Google Professional ML Engineer and AWS Machine Learning Specialty certifications. We guide you on which vendor cert to pursue alongside your Vidyapaath certification.

Ready to Become an ML Engineer?

Enrol in the most comprehensive ML programme in India. Live sessions, mentors and job support included.

💬 Enrol via WhatsApp 🏠 Back to Home
💬