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Enrol now to become a Certified Machine Learning expert with CertZip Machine Learning Masters Program and upgrade your skills.
This Machine Learning Program makes you trained in techniques like Supervised Learning, Unsupervised Learning and Natural Language Processing. Our Machine learning course contains training on the latest advancements and technical approaches in Artificial Intelligence & Machine Learning, such as Deep Learning, Graphical Models and Reinforcement Learning.
A master's in Machine Learning (ML) coursework explores the fundamental mathematics of artificial intelligence and machine learning while enabling students to develop related tools and apply AI and ML to various real-world problems.
Our Machine Learning Course Learning track has been curated after thorough research and recommendations from industry experts. It will help you differentiate yourself with multi-platform fluency and have real-world experience with the essential tools and platforms.
There are no prerequisites for enrolment in the Machine learning Masters Program.
Experienced professional working in the IT industry. An aspirant is planning to enter the data-driven world of Machine Learning.
A machine learning engineer is an engineer that utilizes programming languages such as Python, Java, Scala, etc., to run experiments with the correct machine learning libraries.
As a machine learning engineer working in this branch of artificial intelligence, you'll be accountable for developing programmes and algorithms that allow machines to take steps without being directed.
Machine-learning jobs have jumped by almost 75 per cent over the past four years and are poised to keep growing. Pursuing a machine learning position is a solid choice for a high-paying profession that will be in demand for decades.
understand the fundamental concepts of Python.
learn various types of sequence structures, their use, and perform sequence operations.
learn about different types of Functions and various Object-Oriented concepts such as Abstraction, Inheritance, Polymorphism, Overloading, Constructor, and so on.
Discover how to make generic python scripts, address errors/exceptions in code, and extract/filter content using regex.
basics of Data Analysis utilizing two essential libraries: NumPy and Pandas, the concept of file handling using the NumPy library.
gain in-depth knowledge about exploring datasets and data manipulation utilizing Pandas.
you will learn Data Visualization using Matplotlib.
you will learn GUI programming using the ipywidgets package.
you will get to learn to design Python Applications.
you will learn to design Python Applications.
Understand Machine learning with Python training and see how Data Science helps analyze large and unstructured data with various tools.
structured form, analyzing the data, and representing the data in a graphical format.
you will learn the concept of Machine Learning with Python and its types.
know Supervised Learning Techniques and their implementation, for example, Decision Trees, Random Forest Classifier etc.
learn about the impact of dimensions within data. You will be taught to perform factor analysis using PCA and compress sizes. Also, you will be developing an LDA model.
learn Supervised Learning Techniques and their implementation, for example, Decision Trees, Random Forest Classifier etc.
learns about Unsupervised Learning and the various types of clustering used to analyze and analyze the data.
understand Association rules and their extension towards recommendation engines with the Apriori algorithm.
learn about developing an intelligent learning algorithm such that the Learning becomes more and more accurate as time passes.
know about Time Series Analysis to predict dependent variables based on time. You will be taught different models for time series modelling such that you analyze accurate time-dependent data for forecasting.
