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In this four-week course, you will dive into the basics of machine learning using python; a well-known programming language. Get introduced to data exploration and discover the various machine learning approaches like supervised and unsupervised learning, regression, and classifications and more.
..... Read more34+ Hours of Instructor-Led Sessions
80 Hours of Assignments and MCQs
45 Hours of Hands-On Practice
10 Real-World Live Projects
Fundamentals to an Advanced Level
Code Reviews by Professionals
Data Science has bagged the top spot in LinkedIn’s Emerging Jobs Report for the last three years. Thousands of companies need team members who can transform data sets into strategic forecasts. Acquire the complete machine learning course with Python skills and meet that need.
..... Read moreNot sure how to get started? Let our Learning Advisor help you.
Our immersive learning approach lets you learn by doing and acquire immediately applicable skills hands-on.
Learn theory backed by real-world practical case studies and exercises. Skill up and get productive from the get-go.
Get trained by leading practitioners who share best practices from their experience across industries.
Our Data Science advisory board regularly curates best practices to emphasize real-world relevance.
Webinars, e-books, tutorials, articles, and interview questions - we're right by you in your learning journey!
Six months of post-training mentor guidance to overcome challenges in your Data Science career.
Learn about the various libraries offered by Python to manipulate, preprocess, and visualize data.
Learn Machine Learning with Python, including Supervised and Unsupervised Machine Learning.
Learn to use optimization techniques to find the minimum error in your Machine Learning model.
Learn about Linear and Logistic Regression, KNN Classification and Bayesian Classifiers.
Study K-means Clustering and Hierarchical Clustering.
Learn to use multiple learning algorithms to obtain better predictive performance .
Understand Neural Network and apply them to classify image and perform sentiment analysis.
Learning objectives
In this module, you will learn the basics of statistics including:
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In the Python for Machine Learning module, you will learn how to work with data using Python:
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Get introduced to Applied Machine Learning in Python via real-life examples and the multiple ways in which it affects our society. You will learn:
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Gain an understanding of various optimisation techniques such as:
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In this module you will learn about Linear and Logistic Regression with Stochastic Gradient Descent via real-life case studies
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Learn about unsupervised learning techniques:
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Learn the ensemble techniques which enable you to build machine learning models including:
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Learn to build recommendation systems. You will learn about:
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KnowledgeHut’s Machine Learning with Python certification Course is one of the best machine learning with python courses. This course is focused on helping professionals gain industry-relevant Machine Learning expertise. The curriculum has been designed to help professionals land lucrative jobs across industries. At the end of the course, you will be able to:
Learn Machine Learning with Python through a curriculum designed to suit all levels of Machine Learning expertise. From the fundamentals to the advanced concepts in Machine Learning, the course covers everything you need to know, whether you’re a novice or an expert.
To facilitate development of practical machine learning with python skills, the training adopts an applied learning approach with instructor-led training, hands-on exercises, projects, and activities.
This immersive and interactive workshop with an industry-relevant curriculum, capstone project, and guided mentorship is your chance to launch a career as a Machine Learning expert. The Machine Learning with Python syllabus is split into easily comprehensible modules that cover the latest advancements in ML and Python. The initial modules focus on the technical aspects of becoming a Machine Learning expert. The succeeding modules introduce Python, its best practices, and how it is used in Machine Learning.
The final modules deep dive into Machine Learning and take learners through the learners through machine learning algorithms in python, types of data, and more. In addition to following a practical and problem-solving approach, the curriculum also follows a reason-based learning approach by incorporating case studies, examples, and real-world cases, all in all making it the best machine learning with python course.
Yes, our Machine Learning with Python certification course is designed to offer flexibility for you to upskill as per your convenience. We have both weekday and weekend batches to accommodate your current job.
The complete Machine Learning Course with Python requires daily training hours. In addition to the training hours, we recommend spending about 2 hours every day, for the duration of the course.
There are no prerequisites for attending this Machine Learning with Python certification course, however prior knowledge of elementary Python programming and statistics could prove to be handy.
To attend the complete Machine Learning with Python training program, the basic hardware and software requirements are as mentioned below -
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System Requirements
On adequately completing all aspects of the Machine Learning with Python course, you will be offered a course completion certificate from KnowledgeHut.
In addition, you will get to showcase your advanced Machine Learning with Python skills by working on live projects, thus, adding value to your portfolio. The assignments and module-level projects further enrich your learning experience. You also get the opportunity to practice your new knowledge and skillset on independent capstone projects.
Our introduction to Machine Learning with Python course will give you an opportunity to work on a capstone project. The project is based on real-life scenarios and carried-out under the guidance of industry experts. You will go about it the same way you would execute a Machine Learning project in the real business world.
Learn Machine Learning with Python at KnowledgeHut which is delivered through PRISM, our immersive learning experience platform, via instructor-led training sessions.
Listen, learn, ask questions, and get all your doubts clarified from your instructor, who is an experienced Data Science and Machine Learning industry expert.
The Machine Learning with Python course is delivered by leading practitioners who bring trending, best practices, and case studies from their experience to the training sessions. The instructors are industry-recognized experts with over 10 years of experience in Machine Learning.
The instructors will not only impart conceptual knowledge but end-to-end mentorship too, with hands-on guidance on the real-world projects.
Our Machine Learning with Python workshops are currently held online. So, anyone with a stable internet, from anywhere across the world, can access the course and benefit from it.
Schedules for our upcoming workshops in Machine Learning with Python can be found here.
We currently use the Zoom platform for video conferencing. We will also be adding more integrations with Webex and Microsoft Teams. However, all the sessions and recordings will be available right from within our learning platform. Learners will not have to wait for any notifications or links or install any additional software.
You will receive a registration link from PRISM to your e-mail id. You will have to visit the link and set your password. After which, you can log in to our Immersive Learning Experience platform and start your educational journey.
Yes, there are other participants who actively participate in the class. They remotely attend online training from office, home, or any place of their choosing.
In case of any queries, our support team is available to you 24/7 via the Help and Support section on PRISM. You can also reach out to your workshop manager via group messenger.
If you miss a class, you can access the class recordings from PRISM at any time. At the beginning of every session, there will be a 10-12-minute recapitulation of the previous class.
Should you have any more questions, please raise a ticket or email us on support@knowledgehut.com and we will be happy to get back to you.
Machine Learning and AI have taken the centre-stage as more and more brands realise the possibilities of these tools in the post-COVID world. The demand for data engineers was up 50% and the demand for data scientists was up 32% in 2020 compared to the prior year.
Some of the benefits of learning machine learning with python include the following:
The concept of Machine Learning deals with computers and systems taking in a huge amount of data, analyzing it and solving problems through training on that data in order to obtain the best possible outcome for a task or problem. It is a way for humans to be able to solve problems, without having to actually know and understand what the problem really is, as well as why a particular approach to a problem actually works.
As both machine learning, as well as deep learning are part of the Artificial intelligence domain, their main application is the replacement of decision-making by humans. Some of the popular applications of machine learning and deep learning are:
To complete a Machine learning with Python project:
In order to thoroughly understand the concepts of Machine Learning and to develop successful Machine Learning projects, it is important to know the following:
In theory, you can learn machine learning with python in 3 to 4 months. However, it will take you more than 6 months to practice and get a good grip. Even if the machine learning with python training you have selected is just for 3 months, you need to keep on practising after the course to become an expert in ML.
You do not need a PhD in order to learn Machine learning with Python course. There does not arise a need for you to possess a PhD level understanding of the concepts and applications of Machine Learning, in order for you to take up this course. In the same way that a theoretical Computer Science programmer does not require a background of education in the field of Computer Science, you do not need a very deep and intimate understanding of the theoretical concepts of Machine Learning, in order for you to be able to gain a substantial amount of knowledge about the practical applications of the same.
The complete machine learning course with python involves the fundamentals of machine learning and Python that will help you accelerate your career as a Data science practitioner. At the end of this machine learning with python training, students will be able to:
Before starting a new job, it is important to know and understand the pay scale that that particular career choice offers to you, and how easy (or difficult) it is to obtain a higher salary. In the area of Machine Learning, there exist job opportunities to earn quite a generous salary. However, like most other jobs, the more experience you have higher will be your salary. Generally, the range of salary in the field of Machine Learning can be pegged from 3.5 lakhs per annum for an amateur Machine Learning engineer who is just starting out, to 90 lakhs per annum for an experienced and expert Machine Learning engineer.
Data is transforming everything we do. All organizations, from startups to tech giants to Fortune 500 corporations, are racing to harness the immense amounts of data generated unknowingly every day and put it to use for key decisions. Big and small data is reshaping technology and business as we know it and will continue to do so (in the near future at least).
The state of Machine Learning in companies and in your daily life machine Learning is no more just a mere niche of the tech world but is a new field of work and research altogether. Tech experts have been increasingly making use of Machine Learning over the years. Surge pricing at Uber, Walmart product recommendations, Social media feeds displayed by both Facebook and Instagram, Google Maps, detecting financial fraud at financial institutions etc - all these and many more functionalities are now being performed with the help of powerful Machine Learning algorithms, increasingly without human interference.Every individual is making use of one or the other product of Machine Learning, whether he knows it or not. In such a scenario, learning about Machine Learning is an inevitable step that any professional, especially someone involved in the field of Information Technology and Data Science, must take in order to not become irrelevant.
Some of the benefits of learning Machine Learning include the following:
In order to thoroughly understand the concepts of Machine Learning and to develop successful Machine Learning projects, it is important to know the following:
In theory, you can learn machine learning with python in 3 to 4 months. However, it will take you more than 6 months to practice and get a good grip. Even if the machine learning with python training you have selected is just for 3 months, you need to keep on practising after the course to become an expert in ML.
Machine Learning Algorithms can be classified basically into the following 3 types -
Before starting a new job, it is important to know and understand the pay scale that that particular career choice offers to you, and how easy (or difficult) it is to obtain a higher salary. In the area of Machine Learning, there exist job opportunities to earn quite a generous salary. However, like most other jobs, the more experience you have higher will be your salary. Generally, the range of salary in the field of Machine Learning can be pegged from 3.5 lakhs per annum for an amateur Machine Learning engineer who is just starting out, to 90 lakhs per annum for an experienced and expert Machine Learning engineer.
You do not need a PhD in order to learn Machine learning with Python course. There does not arise a need for you to possess a PhD level understanding of the concepts and applications of Machine Learning, in order for you to take up this course. In the same way that a theoretical Computer Science programmer does not require a background of education in the field of Computer Science, you do not need a very deep and intimate understanding of the theoretical concepts of Machine Learning, in order for you to be able to gain a substantial amount of knowledge about the practical applications of the same.
Although Python is not a necessity for machine learning, it will certainly make your life easier when dealing with Machine Learning concepts and their applications. Python for Machine Learning has several advantages.
Python is one of the most popular languages for the purpose of Machine Learning. At KnowledgeHut, we have curated some of the best resources and videos from all over the internet. Most resources that are included as a part of the advanced machine learning with python course at KnowledgeHut are drawn from some of the top-notch Python conferences such as PyCon as well as PyData etc, created by some of the world’s top Data Scientists, making it one of the best machine learning with python course around the world.
Much of the resources that are offered to learners at KnowledgeHut are hands-on tutorials. These tutorials are all accompanied by extensive code to help participants implement the algorithm or the program taught in that particular tutorial. Real world data sets are also included along with the said tutorials offered by KnowledgeHut.
Thanks to the large and diverse open source community of Python and its libraries, there are some very useful libraries as below:
The following are some tips to help you learn basic Python skills:
SciKit is short for SciPy Toolkit. SciKits are add-on packages for SciPy which are too specialized to be kept in SciPy itself. They are developed and hosted independently from the main SciPy package. One of the most famous SciKit is a scikit-learn package. Below are some of its highlights:
The common steps involved to complete a Machine learning Project with Python include the following:
Due to its vast open-source community, there are tons of libraries for you to play with, but depending upon their ease in implementation, performance, the open source community and so on, we have compiled a list of Python libraries which are best for machine learning.
No, it does not take 2 to 3 hours for setting up Python and its libraries on the laptop. Depending upon the space available on your disk as well as the speed and version of your operating system, the installation of Python and its libraries on your laptop should not take more than 15 minutes.
Below are some major topics that can help you master Machine Learning with Python Course:
The concept of Machine Learning deals with computers and systems taking in a huge amount of data, analyzing it and solving problems through training on that data in order to obtain the best possible outcome for a task or problem. It is a way for humans to be able to solve problems, without having to actually know and understand what the problem really is, as well as why a particular approach to a problem actually works.
As both machine learning, as well as deep learning are part of the Artificial intelligence domain, their main application is the replacement of decision-making by humans. Some of the popular applications of machine learning and deep learning are:
To complete a Machine learning with Python Project with Python:
Whether you're a beginner or advanced, below is the list of free eBooks to help you learn Machine Learning include-
Whether you are a novice or expert at machine learning, videos are a fantastic way to gain more expertise. There is a plethora of free resources available throughout the internet, the most accessible of which is YouTube. But the sheer volume of results that pop up may overwhelm learners.
Here’s a great place to get started with top videos and tutorials on deep learning and Machine Learning
What is Machine Learning | Machine Learning Process and Models | Machine Learning Types | AI and ML