WHAT IS BOOTCAMP?
Bootcamp is an immersion program for learning how to code. A bootcamp promises you an easier path to employment.
A “Coding Bootcamp” is generally a full-time program where students learn skill sets over a fixed period of time.
A coding bootcamp is an intense, accelerated school that aims to teach programming, generally over a course of a few months.
From most coding bootcamps you can expect either:
- Project-based learning
- Group/Pair programming
10 BEST Machine Learning Bootcamps Classes in 2020
The only AI/ML Program in India with a job guarantee.
Machine Learning Career Track: Become an ML engineer in six months.
Price: Rs. 1,95,000 (incl. taxes)
Number of projects: 14 real-world projects
The curriculum is split into 9 units, followed by your capstone project and career advice.
Build job ready skills
Master foundations of data science and choose your focus area: advanced machine learning, natural language processing, or deep learning.
Make yourself hireable with personalized career coaching and 1:1 mentorship from industry experts .
Machine learning is the science of getting computers to act without being explicitly programmed. In the past decade, machine learning has given us self-driving cars, practical speech recognition, effective web search, and a vastly improved understanding of the human genome. Machine learning is so pervasive today that you probably use it dozens of times a day without knowing it.
In this class, you will learn about the most effective machine learning techniques, and gain practice implementing them and getting them to work for yourself.
This course provides a broad introduction to machine learning, datamining, and statistical pattern recognition. Topics include: (i) Supervised learning (parametric/non-parametric algorithms, support vector machines, kernels, neural networks). (ii) Unsupervised learning (iii) Best practices in machine learning.
Machine Learning is a growing field that is used when searching the web, placing ads, credit scoring, stock trading and for many other applications.
This data science course is an introduction to machine learning and algorithms.
You will develop a basic understanding of the principles of machine learning and derive practical solutions using predictive analytics. We will also examine why algorithms play an essential role in Big Data analysis.
Perhaps the most popular data science methodologies come from machine learning. What distinguishes machine learning from other computer guided decision processes is that it builds prediction algorithms using data.
Some of the most popular products that use machine learning include the handwriting readers implemented by the postal service, speech recognition, movie recommendation systems, and spam detectors.
In this course, part of our Professional Certificate Program in Data Science, you will learn popular machine learning algorithms, principal component analysis, and regularization by building a movie recommendation system.
This Specialization from leading researchers at the University of Washington introduces you to the exciting, high-demand field of Machine Learning.
Through a series of practical case studies, you will gain applied experience in major areas of Machine Learning including Prediction, Classification, Clustering, and Information Retrieval.
You will learn to analyze large and complex datasets, create systems that adapt and improve over time, and build intelligent applications that can make predictions from data.
What is machine learning, and what kinds of problems can it solve? What are the five phases of converting a candidate use case to be driven by machine learning, and why is it important that the phases not be skipped? Why are neural networks so popular now?
You will learn how to write distributed machine learning models that scale in Tensorflow, scale out the training of those models. and offer high-performance predictions. Convert raw data to features in a way that allows ML to learn important characteristics from the data and bring human insight to bear on the problem.
Finally, learn how to incorporate the right mix of parameters that yields accurate, generalized models and knowledge of the theory to solve specific types of ML problems.
Interested in the field of Machine Learning? Then this course is for you!
This course has been designed by two professional Data Scientists so that we can share our knowledge and help you learn complex theory, algorithms and coding libraries in a simple way.
We will walk you step-by-step into the World of Machine Learning. With every tutorial you will develop new skills and improve your understanding of this challenging yet lucrative sub-field of Data Science.
Moreover, the course is packed with practical exercises which are based on real-life examples. So not only will you learn the theory, but you will also get some hands-on practice building your own models.
And as a bonus, this course includes both Python and R code templates which you can download and use on your own projects.
Machine Learning and artificial intelligence (AI) is everywhere; if you want to know how companies like Google, Amazon, and even Udemy extract meaning and insights from massive data sets, this data science course will give you the fundamentals you need.
Data Scientists enjoy one of the top-paying jobs, with an average salary of $120,000 according to Glassdoor and Indeed. That’s just the average! And it’s not just about money – it’s interesting work too!
MIT Professional Education is pleased to offer the Professional Certificate Program in Machine Learning & Artificial Intelligence. MIT has played a leading role in the rise of AI and the new category of jobs it is creating across the world economy. Our goal is to ensure businesses and individuals have the education and training necessary to succeed in the AI-powered future.
This certificate guides participants through the latest advancements and technical approaches in artificial intelligence technologies such as natural language processing, predictive analytics, deep learning, and algorithmic methods to further your knowledge of this ever-evolving industry.
This 20-hour Machine Learning with Python course covers all the basic machine learning methods and Python modules (especially Scikit-Learn) for implementing them.
The five sessions cover: simple and multiple Linear regressions; classification methods including logistic regression, discriminant analysis and naive bayes, support vector machines (SVMs) and tree based methods; cross-validation and feature selection; regularization; principal component analysis (PCA) and clustering algorithms.
After successfully completing of this course, you will be able to explain the principles of machine learning algorithms and implement these methods to analyze complex datasets and make predictions in Python.
Machine learning is the study and application of algorithms that learn from and make predictions on data. From search results to self-driving cars, it has manifested itself in all areas of our lives and is one of the most exciting and fast growing fields of research in the world of data science.
This course teaches the big ideas in machine learning: how to build and evaluate predictive models, how to tune them for optimal performance, how to preprocess data for better results, and much more.
caret R package, which provides a consistent interface to all of R’s most powerful machine learning facilities, is used throughout the course.
Learn the core ideas in machine learning, and build your first models.
COURSE LINK HERE
Machine Learning can be an incredibly beneficial tool to uncover hidden insights and predict future trends.
This Machine Learning with Python course will give you all the tools you need to get started with supervised and unsupervised learning.