Who’s this for

Programmers, developers, aspiring data analysts

 

Program Format

Online and masterclasses

Machine Learning with Data Science Training

Machine Learning with Data Science Training To Upskill In-house Talent

Stackroute’s Data Science Program is one-of-a-kind, designed to help enterprises upskill and retain top talent. Best-in-class mentors, robust curriculum, and a window to mastering the most in demand skills, this is an integrated learning experience to fast track career growth. In turn, it helps B2B organizations draw better outcomes across the board. From foundational concepts to working knowledge of real-world tools, here’s an integrated Data Science Course that checks all boxes.

  • tick_imageExposure to working with emerging technologies and in-demand tools like Python, Keras, and TensorFlo
  • tick_imageA chance to learn from passionate and performance-driven Machine Learning and Data Science experts
  • tick_imageAccess to a vibrant and functional community of developers and programmers to stay updated

Your Gateway To A Future-proof Advanced Machine Learning Training Is Here

Discover a one-of-a-kind pedagogy designed for professionals looking to hone their data science and machine learning skills. Stackroute's advanced machine learning program integrates key concepts like applied statistics, advanced regression techniques (Lasso, Ridge), and sophisticated classification methods (AdaBoost, XGBoost). Besides, it also covers regularization practices, effective model tuning strategies (GridSearchCV, RandomSearchCV), and anomaly detection while touching on MLOps, association rule mining, content-based filtering, time series analysis, and foundational neural network architectures (CNN, RNN).

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Self Paced Learning To Keep Up With Your Work Schedule

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The right mix of video-based training and online masterclasses

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A dedicated learning management team

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A seamless, 24/7 support to resolve doubts and queries

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A cohort-based learning system with access to real-time projects

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Industry-leading certification to fast-track your career for future-proof roles

Tools Covered

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Data Science & Machine Learning Courses Mentors

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Talk To Our Program Coordinator

Machine learning and data science Training Preparing You for In-demand Roles

Robust Machine learning and data science Training Preparing You for In-demand Roles

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    Machine Learning Expert: Utilize various machine learning tools and technologies to construct statistical models using extensive business data.

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    Senior Data Scientist: Identify issues, crafts models based on gathered data, and oversees a team of data scientists

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    Applied Scientist: Design and develop machine learning models to enhance intelligence for organizational services and products.

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    AI Expert: Formulate strategies using frameworks and technologies for AI solution development, contributing to organizational growth.

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    Big Data Specialist: Develop and manage adaptable service frameworks for data import, cleansing, transformation, and validation.

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    Senior Business Analyst: Extract data from diverse sources, conducts business analysis, and generates performance reports, dashboards, and metrics for organizational monitoring.

 

Who Should Attend Our Machine Learning Bootcamp Program?

  • Data Scientists and Analysts
  • Software Engineers
  • Business Analysts
  • Programmers and Developers
Who Should Attend Our Machine Learning Bootcamp Program?

Client Testimonials

Trusted By The Best In The Business

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Frequently Asked Questions!

Here are answers to some of the most commonly asked questions by our clients.

1. How can a beginner learn machine learning? groupgroup
Start with foundational knowledge in math, statistics, and programming. Then, learn Python, a commonly used language in ML, and libraries like NumPy, Pandas, and Scikit-Learn. Further, understand ML concepts like regression, classification, and clustering through Stackroute’s machine learning for beginners course. Where you will find several tutorials, mentor guidance and study materials. Practice by working on live projects and participating in StackRoute’s thriving ML communities and competitions.
2. What are the basics of machine learning for beginners?groupgroup
Understand supervised learning (classification, regression), unsupervised learning (clustering), and reinforcement learning. Learn about algorithms like linear regression, decision trees, k-nearest neighbors, and neural networks. Grasp concepts of model training, evaluation, and hyperparameter tuning. Gain hands-on experience with datasets, data preprocessing, and model deployment
3. How do I become an ML data scientist?groupgroup
At the outset, you’ll have to build a strong foundation in mathematics, statistics, and programming (Python, R, SQL). Learn ML concepts, algorithms, and tools like TensorFlow, PyTorch, and scikit-learn. Then, work on your problem-solving skills and the ability to analyze and interpret data. Next, you’ll need to gain practical experience through internships, projects, and Kaggle competitions.
4. Is a machine learning certificate worth it?groupgroup
Definitely! Certificates can validate your skills and knowledge in ML, enhancing your resume. Besides, they can provide structured learning paths and access to industry experts. But practical experience and projects are equally important to build expertise. Certification in Machine Learning from a reputed institution like StackRoute can put you way ahead in the competition for leading roles in an organization.
5. Is Python mandatory for machine learning?groupgroup
Python is highly recommended for ML due to its simplicity, readability, and vast libraries. It offers tools like NumPy, Pandas, and Scikit-Learn essential for data manipulation and model building. While other languages like R and Java are used in ML, Python's popularity makes it a preferred choice.
6. How much Python do I need to know for machine learning?groupgroup
Basic Python knowledge (syntax, data types, control structures) is essential. Familiarity with libraries like NumPy (for numerical operations) and Pandas (for data manipulation) is crucial. Understanding functions, loops, and conditional statements is necessary for writing ML code. Advanced topics like object-oriented programming and decorators may be beneficial for complex ML projects.
7. Is machine learning high paying?groupgroup
ML roles are among the highest-paying in tech due to high demand and specialized skills. Salaries vary based on experience, location, industry, and specific role (ML engineer, data scientist, AI specialist).ML professionals with advanced degrees, certifications, and extensive experience often command higher salaries.

Reach out to us!

Got a question about our programs? Interested in partnering with us? Got suggestions or just want to say hi? Contact us below:

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