Python Machine Learning

Dinesh Raju

Experience: 12+ Year

5.0 5/5 Machine Learning Online Training From Your Home Description Course Curriculum Description

Course Description

Since ML is a subset of AI, the learning curve is steeper when compared to other languages and applications in Computer Science. Apart from being a Software engineer, you would need to have a basic understanding of Statistics, Mathematics, Data Science and a few Programming languages. In fact, once you know the fundamentals of Computers and Software development, it is much easier for you to become an expert in Machine Learning. Machine Learning is one of the most sought-after careers in the market right now and given its potential and a huge scarcity of ML professionals, will remain so at least for the next 2 decades. ML helps explore and analyse huge datasets and reduces the time and effort of Data Scientists. It is useful in several areas such as Image Recognition, Automation, Sentiment Analysis, Banking domain, Language translation, etc. The uses for application of Machine Learning is just evolving and is hence endless. Learning ML throws open plenty of options for a student. You can become a Machine Learning Engineer, Natural Language Processing Scientist, Business Intelligence developer, Computational Linguist, etc. Hence there is a huge demand for machine Learning professionals and since it is a new and evolving field, it is not going to reduce anytime soon. Due to the huge difference in the demand and supply of professionals in Machine Learning worldwide, they are the most sought after by Global IT firms and hence receive the highest pay packages in the industry.

Before understanding Machine Learning and its scope and need for learning, let us understand what is AI or Artificial Intelligence? AI enables the machine to think without human intervention and take a decision on its own. AI is the broader umbrella under which Machine Learning is a subset. Machine Learning or ML provides us a number of statistical tools for data exploration and analysis. It was originally introduced to help in the fields of Statistics, Computer Science and Neuroscience. Machine Learning uses various statistical methods to help machines improve with experience. ML enables us to learn about our world from massive datasets which we, as human beings, with our limited brains cannot interpret and take decisions. It enables computers to look at data and patterns over a period of time and apply them to solve problems in our daily life. Once these patterns are established, it is the job of a Machine Learning Engineer to design, research and implement algorithms and tools. decide and then predict the outcome. They then run machine learning tests and improve models based on these tests. Machine Learning uses several combination skills such as Statistics, Mathematics, Data Science, Programming languages and software engineering. Hence, ML engineers and Data Scientists have to co-operate and work closely with each other to achieve their goals. If you are someone who wants to either enter the IT sector or advance in your career, and want to gain the most of your time and effort, you should learn Machine Learning.

Main features

  • Fundamentals.
  • Advanced Course

Course Curriculum


    • Introduction to Machine Learning
    • What is Machine Learning?
    • Why Machine Learning?
    • Introduction to Big Data and Machine Learning
    • Introduction to Artificial Intelligence and Machine Learning
    • Artificial Intelligence
    • Machine Learning
    • Machine learning algorithms
    • Applications of Machine Learning
    • Python Ecosystem for Machine Learning
    • SciPy, NumPy, Matplotlib, Pandas, Scikit-learn, Machine Learning Techniques.
    • Types of Learning, Supervised learning, Unsupervised learning, Feature scaling, Datasets, Dimensionality reduction


  • For all Graduates
  • Python Basics required

Course Integrated

    • Live Sessions
    • Lab Sessions
    • Free Tutorials
    • Free demos
    • Recorded Videos
    • Resume
    • Mock Interviews
    • Certification
    • Real-time Project Implementation


  • 423 Students Enrolled
  • Duration: 60-65 hours
  • Language: English
  • Sessions: 60+
  • Levels: Beginner to Advanced
  • Time: Online Classes & Weekend Classes
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At Coding Masters, our faculty team is comprised of talented and experienced professionals with several decades of actual work experience in the software industry.

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