Learn machine learning training in San Jose with Python, NumPy, Pandas, Scikit-learn, Matplotlib, Seaborn, TensorFlow/Keras, and Flask for basic deployment. You will work through core ML workflows, model building, data preprocessing, evaluation, and real projects that reflect what employers ask for in San Jose.
14,200+ (Placed)
Freshers to IT
7,100+ (Placed)
Non-IT to Tech
5,800+ (Placed)
Career Gap Fillers
6,400+ (Placed)
Upskilling Success
24,999₹
In 60 Days + Placement
Free Session
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5.2 LPA • ServiceNow Developer
5.7 LPA • Android Developer
6 LPA • Android Developer
7 LPA • Android Developer
9 LPA • AI Engineer
5 LPA • Data Scientist
8 LPA • Machine Learning Engineer
4 LPA • AI Engineer
4 LPA • Associate Product Manager
3.45 LPA • Network Engineer
3.75 LPA • NOC Support Engineer
4.4 LPA • Network Administrator
9 LPA • AI Engineer
12 LPA • Data Engineer
16 LPA • Data Engineer
5.1 LPA • RPA Developer
7.83 LPA • RPA Business Analyst
5.55 LPA • Data Scientist
40 LPA • AWS Devops Engineer
25 LPA • Salesforce Developer
30 LPA • Project Administrator
20 LPA • Digital Marketing Specialist
12 LPA • Social Media Manager
8 LPA • Digital Marketing Analyst
8.5 LPA • Performance Marketer
4.3 LPA • Digital marketing specialist
8 LPA • Performance Marketer
4.3 LPA • AI Engineer
7.5 LPA • Data Engineer
4.5 LPA • Salesforce Developer
8.45 LPA • Computer Vision Engineer
5 LPA • SAP FICO Analyst
5.8 LPA • SAP FICO Analyst
4.2 LPA • Servicenow Developer
4.8 LPA • TOSCA Automation Engineer
8 LPA • Data Engineer
8 LPA • Tosca Test Analyst
10 LPA • Machine Learning Engineer
4.4 LPA • Tosca Administrator
5.7 LPA • ML Engineer
6 LPA • Devops Engineer
7.15 LPA • DevSecOps Engineer
6.3 LPA • AI Engineer
7 LPA • MLOps Engineer
5 LPA • HR Executive
7 LPA • Data Scientist
10 LPA • Brand Marketing Specialist
8.2 LPA • AI Engineer
Learning machine learning is only part of the job search. Inventateq supports learners in San Jose with practical placement help so they can present their Python, ML, and deployment skills clearly to employers and hiring managers.
San Jose hires across software, cloud, analytics, AI product, and data teams. Pay grows with experience as learners move from trainee and analyst roles into machine learning engineering, MLOps, and architecture work.
Machine Learning Average Salary by Experience
San Jose hires across software, cloud, analytics, AI product, and data teams. Pay grows with experience as learners move from trainee and analyst roles into machine learning engineering, MLOps, and architecture work.
Machine Learning Average Salary by Experience
4.7/5 Google Rating | 1,432+ Verified Reviews
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By Justdial
4.7 / 5
By Sulekha Courses
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Success Result: Our students are competing at global levels. Watch their placement journey here.
Data Engineering @ Accenture - 12 LPA
Junior Accountant @ Fortis - 8 LPA
SQL Developer @ Wipro - 10 LPA
Salesforce Administrator @ Deloitte - 15 LPA
RPA Developer @ IBM - 20 LPA
Tableau Developer @ Genpact - 20 LPA
Talent Acquisition Executive @ Tech Mahindra - 12 LPA
Angular Developer @ Capgemini - 15 LPA
Data Analyst @ Amazon - 25 LPA
Java Developer @ Oracle - 25 LPA
CATIA Design Engineer @ TATA Motors - 20 LPA
AWS Solutions Architect @ Accenture - 25 LPA
Python Developer @ Mphasis - 15 LPA
QA Engineer @ HCLTech - 15 LPA
Cloud DevOps Engineer @ LTIMindtree - 18 LPA
Digital Marketer @ Google - 20 LPA
BTM Layout @ Inventateq - -
Genuine Reviews @ Inventateq - 25 LPA - 50LPA
Data Engineering @ Accenture - 12 LPA
Junior Accountant @ Fortis - 8 LPA
SQL Developer @ Wipro - 10 LPA
Salesforce Administrator @ Deloitte - 15 LPA
RPA Developer @ IBM - 20 LPA
Tableau Developer @ Genpact - 20 LPA
Talent Acquisition Executive @ Tech Mahindra - 12 LPA
Angular Developer @ Capgemini - 15 LPA
Data Analyst @ Amazon - 25 LPA
Java Developer @ Oracle - 25 LPA
CATIA Design Engineer @ TATA Motors - 20 LPA
AWS Solutions Architect @ Accenture - 25 LPA
Python Developer @ Mphasis - 15 LPA
QA Engineer @ HCLTech - 15 LPA
Cloud DevOps Engineer @ LTIMindtree - 18 LPA
Digital Marketer @ Google - 20 LPA
BTM Layout @ Inventateq - -
Genuine Reviews @ Inventateq - 25 LPA - 50LPA
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4.7/5 · 1,432+ Verified Reviews
Inventateq teaches machine learning in a practical order: Python first, then preprocessing, core algorithms, evaluation, feature engineering, and deployment basics. The course is built around the actual tools used in the syllabus, including Python, Pandas, NumPy, Scikit-learn, TensorFlow/Keras, and Flask.
We stand apart through our commitment to:
Live online machine learning training is available for learners in San Jose who want to study from home or balance work with learning. The sessions stay interactive, with trainer-led explanations, coding practice, and project support across the same syllabus covered in class.
Good for learners who want a structured start in machine learning, Python, and data preprocessing.
Useful for analysts, developers, and engineers who want to move into ML and AI roles.
Helps build job-ready skills for data, ML intern, and junior engineer roles.
Suitable if you are ready to learn Python, statistics, and model building step by step.
Fits learners aiming for ML, data science, and AI roles in the San Jose job market.
Mode: Offline classroom and live online options
Delivery: Instructor-led practical sessions
Pace: Step-by-step learning from basics to projects
Support: Doubt clearing during and after sessions
No prior machine learning experience is required to start.
Rated 4.9/5
Inventateq focuses on practical machine learning training that follows the real course syllabus, not filler content. Learners build skills in Python, preprocessing, supervised and unsupervised learning, evaluation, feature engineering, and basic deployment.
This course gives you applied practice in Python, Scikit-learn, TensorFlow/Keras, and Flask basics. By the end, you will have project experience you can discuss in interviews and add to a portfolio.
You will work with datasets, clean them, prepare them, and train models for prediction and classification.
You will learn how ML projects move from data collection and preprocessing to evaluation and deployment basics.
You will use regression, trees, SVM, clustering, PCA, and anomaly detection concepts in a structured way.
You will learn feature engineering, imbalance handling, cross-validation, and ways to reduce overfitting.
Projects like house price prediction and spam detection give you proof of practical skill.
Resume building and interview preparation are included so you can speak about your work clearly.
The certification validates that you have completed structured training in machine learning fundamentals, Python-based model building, evaluation, and deployment basics. It helps employers see that you have studied a practical syllabus and worked with the tools used in real ML projects.
Earn this certificate upon successful completion of our training program.
Validate your skills with recognized industry credentials.
Earn this certificate upon successful completion of our training program.
Validate your skills with recognized industry credentials.
Yes. The course starts with machine learning basics, Python for ML, and the core math and statistics you need. You can join even if you are new to the subject, as long as you are ready to follow the practice sessions step by step.
Yes. The syllabus includes real-time projects such as house price prediction, spam email detection, customer segmentation, and disease prediction. These projects are important because they help you apply the concepts instead of only learning theory.
Yes. Placement support includes resume help, interview preparation, portfolio guidance, and role targeting. The support is aimed at helping you apply for machine learning, data science, and analyst roles after course completion.
Yes, if they are willing to learn Python, basic statistics, and ML concepts from the beginning. The course is designed to build the foundation before moving into algorithms and project work. That makes it easier for learners from non-technical backgrounds to keep up.
Yes. You can attend live online sessions from San Jose and learn the same syllabus covered in the classroom format. This is useful if you want flexibility while still getting trainer-led practice and doubt clearing.
The training follows the full syllabus from fundamentals through deployment basics and projects, so the duration depends on the batch format you choose. The course is paced to cover each module properly rather than rushing through topics. You can confirm the current batch schedule with Inventateq.
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