Machine Learning Course by Great Learning: A Future to Rely On
Machine learning is one of the most exciting careers that you could choose. Machine learning is considered as one of the fastest-growing technologies. But, what exactly is machine learning? Machine learning is a subset of artificial intelligence that renders systems the skill to spontaneously learn and progress from experience without being specifically instructed. The term Machine Learning was coined in 1959, by Arthur Samuel.
Why Machine Learning?
Machine learning has shown a great impact on many industries that have been applied such as health care, transportation, finance, logistics, etc. Machine learning is growing rapidly day by day and this offers various job roles as many industries are accommodating machine learning practices. With the help of Machine Learning, businesses can automate routine tasks. It helps in creating models that are capable of processing large amounts of complex data and providing accurate results. The Machine Learning market is estimated to reach USD 8.81 billion by 2022, thus, making it the perfect opportunity for you to take up a machine learning course online now. Upskilling will let you enter the market well prepared.
Pursuing a Machine Learning online certification course can help you be an active part of the digital revolution we talk about in sectors ranging from healthcare to retail, logistics, manufacturing, and so on. Having ML skills makes you a hot resource in any sector, which leaves a lot of open avenues for you to choose from.
Importance of Machine Learning
The techniques used in deep learning or deep neural networks have been around for many years. These techniques weren't this effective in the early days. While in recent years, the practice of tools and techniques of machine learning has dramatically increased. Machine learning when applied to the right data results in great breakthroughs. The quality of the machine learning outputs has been extremely appreciable. Machine learning will stand as a game-changer in every field that is applied.
Getting the tasks done by computers such as image recognition, translation, speech recognition, etc is a major technological upgrade. Machine learning has made human lives easy. The advances in machine learning will make a big difference in many fields where it has been applied.
What are the top Machine Learning practising companies in India?
Machine learning has become a go-to technology for almost every industry today, and rightly so. From gaming to healthcare, almost every industry today is making use of Machine Learning. Image recognition, text generation, and many other use cases are increasing the scope of Machine Learning professionals today. It not only helps in automating processes but also ensures error-free results. This is a great advantage for any organisation. It allows businesses to leverage data and create business solutions that are tailored to their requirements.
India has seen a steady growth in Machine Learning companies in recent years. There is no such set of companies that alone practice machine learning, but many top companies such as Genpact, Flipkart, Apple, Amazon, Google, etc are thoroughly applying machine learning practices in their day-to-day work.
Who is a Machine Learning Engineer?
Before getting deep into the roles and responsibilities of a machine learning engineer, first, let us understand who exactly is a machine learning engineer? A Machine learning engineer can be defined as highly skilled programmers that develop algorithms that help the system to analyze and take decisions without being given specific directions.
Apart from programming, Machine Learning engineers are also responsible for customising data sets for analysis, personalising web experiences, identifying and predicting business requirements. Hiring companies typically look for candidates with a master’s degree and a few years of experience in similar roles. So taking up online ML courses might be a great option if you want to venture into the field of Machine Learning.
How to become a Machine Learning Engineer?
If you are keenly interested in becoming a machine learning engineer, let us talk about how to start learning machine learning? Taking up the machine learning course would be the most preferable decision you could make to become a machine learning engineer. ML online training will help you attain a perfect understanding of all the concepts of machine learning you got to learn machine learning from scratch, which is a tough task. But few prerequisites help to make machine learning an easy task.
Machine Learning Engineer Skills
A machine learning course online will teach you the relevant skills required for you to become a Machine Learning engineer. The skills required are as follows.
Programming Language Knowledge: One of the key skills required is the knowledge of any programming languages. Python, R, Java, and C++ are the commonly known programming languages, where Python stands as the most widely used language. Python is known for its flexibility and versatility. A python machine learning course online is important if you want to grow in the field of ML.
Probability and Statistics: Linear Regression, standard deviation, Naive Bayes, probability theory are all important skills that Machine Learning engineers need to be adept in. This will help Machine Learning engineers adapt to the uncertainties of real-world challenges. Hypothesis testing and ANOVA are important skills to learn too. The top machine learning courses online will cover these topics and help you gain a better understanding.
Data Modeling & Evaluation: This helps Machine Learning professionals in creating or estimating the structures of any given dataset. This process helps in identifying patterns (clusters, correlations, etc), predicting properties (classification, anomaly detection, regression), and creating the analysis models accordingly.
Distributed Computing: Apache Hadoop and cloud services such as Amazon EC2 comes in handy and is an important skill to acquire. An applied machine learning online course can help you master these skills.
Machine Learning Algorithms and Libraries: ML libraries and various packages are available online, but they are not suitable for all kinds of applications. An important skill to learn is how to apply these libraries effectively and optimize the outcome. Awareness of the advantages and disadvantages is necessary.
If you are yearning to start a career in machine learning and haunting the best way to learn machine learning, this page will surely lead you to find the best place to learn machine learning.
Roles and Responsibilities of a Machine Learning Engineer
Study and transform Data Science prototypes
Data science has become essential across a wide range of industries in recent years. Data science has developed a set of rules to understand human intelligence, which is popularly known as artificial intelligence. The practices of artificial intelligence would help to add real value to the business. A machine learning engineer has to study and transform all the prototypes.
Design an Effective Machine Learning System
Designing a production-ready machine learning system is one of the major responsibilities that a machine learning engineer has. Machine learning engineers need to learn the principles of reactive design, and they will have to build pipelines that are creative with highly scalable.
- Research and Implement appropriate Machine Learning Algorithms
When you keenly observe machine learning algorithms, there is no one particular algorithm that fits every problem. Several factors affect when you choose an inappropriate machine learning algorithm. Specific problems that are unique, desire an indifferent approach to solving them while some other problems are open to the trial and error process.
There are basically three types of machine learning algorithms.
- Reinforcement learning
- Develop Machine Learning applications according to the requirements
Machine learning results will always be based on the algorithms that a machine learning engineer generates. So, the development of machine learning applications requires a collection of advanced languages, programming tools that are accessible by the developers.
- Select appropriate data sets and data representation methods
This is the most typical role played by the machine learning engineer. It involves major responsibility along with high risk as well. Using the data collected during operation, it requires an understanding of basic mathematics and statistics. Besides applying the tools required for analysis such as Python, R, Matlab, etc, and the tools required for visualization. It also requires an understanding of databases such as SQL.
Making sure about the data that needs to be considered to generate algorithms, the reporting plays a major role as the data that you choose decides the output.
- Test and Experiments
Machine learning experiments do consume a lot of time and effort. To perform discrete experiments, you must be efficient in analyzing the reasons for the test failures. Carefully planning and organizing the type of experiments that you decide to run is the most important task.
- Perform Statistical Analysis
Performing statistical analysis is another important role and responsibility of a machine learning engineer. Statistical and machine learning are closely related to each other. Statistical analysis helps to retrieve effective machine learning results.
Why choose Great Learning for your Machine Learning course?
Machine Learning Online Training will enable you to achieve your career aspirations. Each course curated by Great Learning features a hands-on lab experience. This helps you learn, as well as apply the highly critical skills in the field of Machine Learning. The best way to learn machine learning online is through a comprehensive course, exactly what we offer here at Great Learning. The benefits of opting for the Machine Learning course by Great Learning include:
Learn at your own pace : All our courses can be availed online and can be studied at any time online depending on your schedule. Regardless of whether you have plans to spend a few hours every day or use your weekends to get through this course, we have just the right syllabus for all. With a good internet connection and phone/tablet, you can view all our video courses in the Machine Learning tutorials. So study machine learning online at your own pace, without any time constraints.
Get International Recognition : Learn ML online and on successful completion, get a Machine Learning certificate from The University of Texas at Austin, along with the prestigious Great Lakes Executive Learning which is ranked among Indias' top 10 Business Schools.
Learn by doing : The ML online course follows a rigorous hands-on approach. Students are asked to participate in case studies, real-life business problems, mini-projects, and more. Each student is provided with a mentor and guidance throughout the machine learning online class.
Corporate partnership or industry exposure : Can be known as the best course to learn Machine Learning because it gives the students an\ opportunity to learn from some of the industry’s leading minds. Industry experts participate in guest lectures and mentor candidates in their capstone projects to ensure a thorough understanding of the current scenario in the industry.
Machine Learning Books : Machine Learning includes various concepts such as statistics, linear algebra, calculus, and many more. The sheer vastness of the subject paves the way for unlimited possibilities. While deep learning online courses, machine learning beginners course, other such online courses are a great way to acquire knowledge, books are another way to do so. One of the best ways to continue learning on the go is to read books written by experts in the field. Reading more books will also help you gain perspective into different viewpoints. You can understand the different approaches that are being taken to address the same problem and compare these approaches to choose the best solution. Here’s a list of the top ML books that will help you deep dive into concepts and apply them to your work.
A day in the life of an ML Engineer- Here’s what it looks like
- Check the models that have been active for a while
- Connect with the rest of the team for updates
- Look through task management platforms to schedule the day
- Analyse company codebase using Scikit learn to look for bugs
- Code with PyCharm to implement a model or keep the interfaces of a database running
- Meet stakeholders to ensure products are updated with new features and changes are implemented according to plans
- Discuss how to optimize products and create plans and processes for it
- Research on the latest trends in the domain and how the company can benefit from it
How to Become a successful ML practitioner?
Step 1. Understanding the fundamentals
Step 2. Learn ML online
Step 3. Refer to some good books
Step 4. Learn algorithms
Step 5. Test your learning
Future Scope of Machine Learning
To conclude, let us take a look at what the future holds for Machine Learning. It is estimated that the Machine Learning market will grow to reach USD 8.81 billion by the year 2022. This means that there will be a substantial requirement of skilled professionals in this field. The future looks promising for those taking up a machine learning online certification. Great Learning provides one of the best Machine Learning courses online if you’re interested in learning more about the field and are interested in pursuing a career in Machine Learning, join our course today.