1. Machine Learning Basics (Week 1)
- •Introduction to machine learning
- •Supervised, unsupervised, and reinforcement learning
- •Real-world use cases
- •Difference between AI, ML, and data science
- •Overview of the ML workflow
Learn machine learning in Pune with Python, NumPy, Pandas, Scikit-learn, Matplotlib, Seaborn, TensorFlow/Keras, and Flask basics. Build a solid path from data preparation and model training to evaluation and simple deployment, using the tools listed in the course syllabus.
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Learning machine learning is only part of the goal. Inventateq adds placement support so you can present your work clearly, speak about your projects with confidence, and apply for roles that match your skill level in Pune.
Pune hires for machine learning across IT services, product teams, analytics, fintech, healthcare, and automation work. Salary grows as you move from model building and analysis into deployment, scaling, and team ownership.
Machine Learning Average Salary by Experience
Pune hires for machine learning across IT services, product teams, analytics, fintech, healthcare, and automation work. Salary grows as you move from model building and analysis into deployment, scaling, and team ownership.
Machine Learning Average Salary by Experience
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Inventateq keeps the course practical from the start. You learn machine learning concepts, Python libraries, statistics, preprocessing, supervised and unsupervised learning, model evaluation, feature engineering, and deployment basics through structured sessions and projects that follow the syllabus.
We stand apart through our commitment to:

Live online classes are available for learners in Pune who want structured machine learning training from home or work. You still get interactive sessions, project guidance, and support on Python, Scikit-learn, TensorFlow/Keras basics, and deployment topics.
Good for learners starting with Python and wanting a practical entry into machine learning.
Useful for analysts and IT professionals who want to move into data and ML roles.
Suitable if you are ready to learn Python, data handling, and core ML concepts step by step.
Helps you strengthen preprocessing, model evaluation, and prediction skills.
Helpful for people aiming for machine learning, data science, or AI developer roles.
Mode: Offline classroom and live online training
Language: Practical instructor-led sessions
Format: Concepts, coding practice, and projects
Support: Doubt clearing and mentor guidance throughout
No prior machine learning background is required. The course starts from the basics and moves step by step.
Rated 4.9/5
Inventateq focuses on job-ready machine learning skills, not just theory. The training follows the syllabus closely so you move from Python and data handling to model building, evaluation, and deployment basics in a clear sequence.
You work with the same tools and workflows used in entry-level machine learning jobs. By the end, you can clean data, train models, evaluate results, and explain your work in interviews.
Work on house price prediction, spam detection, customer segmentation, and disease prediction. These projects help you understand how machine learning is applied to real datasets.
Learn preprocessing, encoding, scaling, feature selection, and outlier handling. This gives you a base that is useful in both analyst and machine learning roles.
Practice regression, classification, clustering, and basic neural network concepts. You learn how to test models and compare results using clear metrics.
Use accuracy, precision, recall, F1 score, confusion matrix, cross validation, and bias-variance concepts. This is important for improving model quality.
Get an introduction to Flask, FastAPI, APIs, cloud deployment, and model monitoring. You understand how ML models move beyond notebooks.
Resume building and interview preparation are part of the final stage. You learn how to present your project work and explain your ML choices clearly.
The certification confirms that you have completed structured training in machine learning concepts, Python-based model building, preprocessing, evaluation, and basic deployment. It helps show employers that your learning is tied to practical work, not only theory.
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 is suitable for beginners who want to learn machine learning from the ground up. It starts with the basic concepts and then moves into Python tools, statistics, preprocessing, and model building. If you can follow structured classes and practice coding, you can join.
Basic programming awareness helps, but it is not mandatory. The course covers Python basics for machine learning along with NumPy, Pandas, and notebook practice. That means you can build the required foundation during the training itself.
Yes, the course includes real-time projects such as house price prediction, spam email detection, customer segmentation, and disease prediction. These projects are useful because they connect the theory to actual datasets and model building. They also help when you prepare your resume and interviews.
Yes, placement support is included. You get resume help, mock interviews, portfolio guidance, and career mentoring for roles such as machine learning trainee, data analyst, and junior data scientist. The support is practical and tied to your project work.
Yes, live online training is available for learners in Pune. It is useful for working professionals who want structured sessions without commuting. You still get interactive guidance, project help, and support on the core tools used in the course.
The main tools covered in the syllabus are Python, Jupyter Notebook, Scikit-learn, Pandas, NumPy, Matplotlib, Seaborn, TensorFlow/Keras basics, and Flask for deployment basics. The broader tools list also supports deeper exposure to ML workflows and modern platforms. This gives you a strong practical base for beginner to junior-level roles.
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