Machine Learning Training Bootcamp Course

Machine Learning is one of the fastest evolving fields, it involves different algorithms which businesses can utilize for developing their projects. Machine learning algorithms are implemented using various languages such as C, C++, JavaScript, R, and Python.

Machine Learning (ML) is expected to bring heavy changes to the world of technology. Machine learning is a subfield of artificial intelligence and computer science that allows software applications to be more accurate in predicting results.

Machine Learning Training Quality Software Technologies

Machine Learning Course

This course will help you Master Machine Learning in Python.
One of the best parts about our Machine Learning course is that The topics covered in the course include supervised learning, best practices, you also get to encounter numerous case studies and applications among a host of other things
With a broad overview of the discipline’s most common techniques and applications, you’ll gain more insight into the assessment and training of different machine learning models.

Python Programming For ML

Python programming language can be found practically at every place, like web and desktop apps, machine learning, network servers, and many more. It is one of the fastest-growing programming languages. Python programming language has several advantages which enable Machine Learning developers to use it for developing their Machine Learning projects.

Python is the tool of choice for people who want to explore and apply machine learning for their research projects – data analysis, pattern recognition, etc. Python comes with several very attractive machine learning libraries which can be applied out of the box.

Python is one of the most popular programming languages in the world. Favored for applications ranging from web development to scripting and process automation, Python is quickly becoming the top choice among developers for artificial intelligence (AI), Machine learning, and deep learning projects.


  1. Use Python for Data Science and Machine Learning
  2. Use Spark for Big Data Analysis
  3. Implement Machine Learning Algorithms
  4. Learn to use NumPy for Numerical Data
  5. Learn to use Pandas for Data Analysis
  6. Learn to use Matplotlib for Python Plotting
  7. Learn to use Seaborn for statistical plots
  8. Use Plotly for interactive dynamic visualizations
  9. Use SciKit-Learn for Machine Learning Tasks
  10. Algorithms
  11. K-Means Clustering
  12. Logistic Regression, Linear Regression
  13. Random Forest and Decision Trees
  14. Natural Language Processing and Spam Filters
  15. Neural Networks
  16. Support Vector Machines
Key Features

Courses that help you grow

Industry leading Trainers
Learn from professionals who have years of teaching experience
Always Updated Curriculum
Our syllabus is updated to match the demands of the industry
Full Placement Support
We provide 100% placement support on all our courses

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We truly care for our students that's why we provide full support even after you have been placed in a company after completing a course.