Machine Learning for Java Developers
Machine Learning is the crux of Artificial Intelligence. And with increasing developments in AI, IoT and other smart technologies, machine learning jobs are gaining higher value and demand in the market. This course is specifically designed to achieve Machine Learning basics for beginners. Enroll in this Machine Learning basic course and get a good hold of the Machine Learning concepts.
Machine Learning for Java Developers is a Virtual Instructor-Led online course. In this course you will learn the Basics of Machine Learning. This course will get you up and running quickly, providing you with the skills that you need to successfully create, customize, and deploy machine learning applications in real life.
This course will teach you how to create and implement machine learning algorithms in Java by providing fundamental concepts as well as practical examples. It would be helpful to be a little familiar with basic programming and data mining concepts, but no prior experience with data mining packages is necessary.
Why take up this course?
- The demand for Machine Learning is at an all-time high. With every industry looking to apply AI in their domain, studying machine learning opens a world of opportunities to develop cutting edge machine learning applications in various verticals – such as cyber security, image recognition, medicine, or face recognition.
- The average starting salary of a Machine Learning Engineer is minimum INR 25L per year.
- People who have Machine Learning skills will have great demand in the IT industry. Our online instructor led training will help you learn these skills and hence upgrade your career.
Course Objectives
After attending this course, learner’s will be able to demonstrate the following skills:
- Learn and understand fundamentals of Machine Learning.
- Learn how to identify appropriate problems, use cases for machine learning.
- Learn how to use machine learning tools to gain insights from your data.
- Learn how to prepare data for analysis, choose a machine learning method, and evaluate your machine learning models using the right evaluation metrics.
- Linear Regression, Logistic Regression, and Decision Trees algorithms for building machine learning models.
- Understand how to solve Classification and Regression problems using machine learning.
- Learn different performance improvement techniques, including input preprocessing and combining output from different methods.
Who should attend this course?
- Candidates aspiring to be a Data Scientist, Data Engineer, Data Analyst, Data Analytics Professional, Software Developer.
- Fresh Graduates who are looking to build a career in Data Science and Machine Learning
- Enterprise Architects, Managers, CXOs planning to shift to Big data tools in their organisation.
- Technical professionals and others with technical background that work with large amounts of data and want to take advantage of Machine Learning to improve decision-making processes.
Course Highlights
Advanced Curriculum
Designed by subject specialists and reviewed by industry experts
Interactive Learning
Engaging content, easy to learn with no prior experience required
Discussion Forums
Ask questions and engage in discussions with instructors and other learners
Hands-on Lab Sessions
Practice Labs are available 24/7 for hands-on skill development
Real Life Case Studies
Learn about use cases, solution, challenges, best practices and lot more
Career Mentoring
Get continuous guidance on your career advancement from experts
Guaranteed Job
Guaranteed Job Placement through our network of 450+ Hiring Partners across Pan India
24/7 Tech Support
Get 24/7 full technical support even after you have completed the course
Lifetime Access
Get lifetime access to course material, presentations, videos etc
Post Program Career Options
Average Salary Trends
Hiring Companies
What are the Prerequisites for this course?
There is no specific prerequisite to learn machine learning. But you need to be from an Engineering/Science/Maths/Stats background to understand the concepts and the techniques used.
Please note that the sessions will be conducted via google meet and require an Internet Connection and headset with microphone connected to your computer or laptop.
Upcoming Batches
Batch Start Date | Course Duration | Class Timings |
September 30th 2023 | SAT & SUN (12 WEEKS) WEEKEND BATCH | FEW SEATS LEFT. HURRY UP 10:00 AM to 13:00 PM (IST) |
October 9th 2023 | MON, WED, FRI (12 WEEKS) EVENING BATCH | 08:30 PM to 10:30 PM (IST) |
October 14th 2023 | SAT & SUN (12 WEEKS) WEEKEND BATCH | 10:00 AM to 13:00 PM (IST) |
October 16th 2023 | MON, WED, FRI (12 WEEKS) MORNING BATCH | 06:00 AM to 08:00 AM (IST) |
October 23rd 2023 | MON, WED, FRI (12 WEEKS) EVENING BATCH | 08:30 PM to 10:30 PM (IST) |
Course Certification
Sample Certificate
Module 1.0 : Introduction to Machine Learning
1
1.1 : What is Artificial Intelligence?
2
1.2 : How does AI solve real world problems?
3
1.3 : Why Machine Learning?
4
1.4 : Problems Machine Learning Can Solve
5
1.5 : Big Data in Context of Machine Learning
6
1.6 : Why Java?
7
1.7 : Machine Learning Libraries and Tools
8
Skill Test
Module 2.0 : Supervised Learning and Linear Regression
1
2.1 : Classification and Regression
2
2.2 : Generalization, Overfitting, and Underfitting
3
2.3 : Relation of Model Complexity to Dataset Size
4
2.4 : Supervised Machine Learning Algorithms
5
2.5 : k-Nearest Neighbors
6
2.6 : Linear Models
7
2.7 : Naive Bayes Classifiers
8
2.8 : Decision Trees
9
2.9 : Ensembles of Decision Trees
10
2.10 : Kernelized Support Vector Machines
11
2.11 : Neural Networks (Deep Learning)
12
2.12 : Uncertainty Estimates from Classifiers
13
2.13 : The Decision Function
14
2.14 : Predicting Probabilities
15
2.15 : Uncertainty in Multiclass Classification
16
Skill Test
Module 3.0 : Unsupervised Learning and Preprocessing
1
3.1 : Types of Unsupervised Learning
2
3.2 : Challenges in Unsupervised Learning
3
3.3 : Different Kinds of Preprocessing
4
3.4: Applying Data Transformations
5
3.5 : Scaling Training and Test Data the Same Way
6
3.6 : The Effect of Preprocessing on Supervised Learning
7
3.7 : Principal Component Analysis (PCA)
8
3.8 : Non-Negative Matrix Factorization (NMF)
9
3.9 : Manifold Learning with t-SNE
10
3.10 : Clustering
11
Skill Test
Module 4.0 : Representing Data and Engineering Features
1
4.1 : Binning, Discretization, Linear Models, and Trees
2
4.2 : Interactions and Polynomials
3
4.3 : Univariate Nonlinear Transformations
4
4.4 : Automatic Feature Selection
5
4.5 : Univariate Statistics
6
4.6: Model-Based Feature Selection
7
4.7 : Iterative Feature Selection
8
Skill Test
Module 5.0 : Model Evaluation and Improvement
1
5.1 : Cross-Validation in scikit-learn
2
5.2 : Benefits of Cross-Validation
3
5.3 : Grid Search
4
5.4 : Evaluation Metrics and Scoring
5
5.5 : Metrics for Binary Classification
6
5.6 : Metrics for Multiclass Classification
7
5.7 : Regression Metrics
8
5.8 : Using Evaluation Metrics in Model Selection
9
Skill Test
Module 6.0 : Algorithm chains and Pipelines
1
6.1 : Parameter Selection with Preprocessing
2
6.2 : Building Pipelines
3
6.3 : Using Pipelines in Grid Searches
4
6.4 : The General Pipeline Interface
5
6.5 : Grid-Searching Preprocessing Steps and Model Parameters
6
6.6 : Grid-Searching Which Model To Use
7
Skill Test
Module 7.0 : Working with Text Data
1
7.1 : Types of Data Represented as Strings
2
7.2 : Representing Text Data as a Bag of Words
3
7.3 : Stopwords
4
7.4 : Rescaling the Data with tf–idf
5
7.5 : Investigating Model Coefficients
6
7.6 : Advanced Tokenization, Stemming, and Lemmatization
7
7.7 : Topic Modeling and Document Clustering
8
Skill Test
Module 8.0 : Wrapping up
1
8.1 : Approaching a Machine Learning Problem
2
8.2 : From Prototype to Production
3
8.3 : Testing Production Systems
4
8.4 : Building Your Own Estimator
5
8.5 : Where to Go from Here
6
Skill Test
The advantages of doing a course from Oxzer Academy are multifold.
Our Instructors are professional trainers who have extensive technology and domain experience, including years of experience training & mentoring professionals in the industry.
You get lifetime access to course material including presentations, videos etc.
You get the industry recognised certificate from Oxzer Academy on your successful course completion.
We give you an option to attend a free trial class before enrolling in the course.
We provide 24 * 7 online support to resolve all your technical queries even after you have completed the course.
We provide flexible batch timings to suit your availability. Most classes are scheduled either on weekends or in the evening hours, so that the class timings do not overlap with your other work during the day time.
In case you miss any class, in that case you can go through the recorded videos of that lecture. Also there is an option to attend the lecture in a different batch if there is a seat available.
Every module in the course will be followed with a quiz to assess your learning.
We give you extensive time to complete the hands-on labs and assignments.
We have smaller batches with a limited number of people in a single batch to ensure quality learning.
This is a Virtual Instructor Led training (VILT) where an instructor will facilitate a training session for a group of learners over a virtual setting (online mode). Similar to traditional instructor-led classroom training, VILT is synchronous, collaborative, and happens in real-time.
This is a virtual online Instructor Led course. There will be a maximum of 20 learners in a single batch.
Yes, the course curriculum includes both hands-on lab and theory sessions as well. The hands-on labs will be continuously monitored by our instructor and you get sufficient time to complete your labs. It is mandatory for the learners to attend both the labs as well as theory sessions for successful course completion.
All our labs are provisioned in the cloud. So you can only access the labs during the duration of the course. Ideally, once you have completed your course, your lab access will be removed as well. But in exceptional cases where you need extension for an additional time, you can drop an email to helpdesk@oxzeracademy.com or open a support ticket with our helpdesk regarding this. Once your request has been considered and approved by management, you will receive an email notification within 48 hours from Oxzer Academy providing you with the status on the lab extension. You can request for extension only once.
The online classes will happen on google meet or similar communication platform. You will be notified with the login details before every class.
Yes, you are eligible for one free trial class. You can attend your first class as a trial class. Please note that there is only one trial class provided for each course.
There is only one trial class provided under this course.
Yes, classes are structured in batches and each batch has a specific time. You can enrol yourself in a batch which suits your availability. If you are not able to attend the lecture due to any specific reason then you can go through the recorded videos of that lecture. Also there is an option to attend the lecture in a different batch if there is a seat available.
No, certification exam fee is not included in the course fees. If you wish to appear for the certification exam after course completion, then you need to enrol separately for the certification exam. Please note that any payments which are done on the third party websites, then the terms and condition, refund policy etc of the third party website will be applied.
No, there will be no refund in such cases. Please read the Refund policy carefully before enrolling in the course. https://www.oxzeracademy.com/refund-policy/
We have a 24/7 help desk to support our learners, instructors, customers and partners. You can raise a support ticket to our help desk from this page https://www.oxzeracademy.com/submit-ticket/ Additionally, you can find our contact information on our website https://www.oxzeracademy.com
Oxzer Academy will review the complaint within one hour of submission and will also take necessary action within 24 hours on the posted complaint if required.
There are various channels through which the learners and instructor interact in an online class. Learners can post his question in the google meet or similar communication platform chat and the instructor will respond. Then the learner can raise his hand, unmute himself and can directly ask questions to the Instructor. Also, towards the end of every lecture, there will be a query session for 15 minutes in which the learner can ask any doubt from the Instructor.
No, all our classes will be delivered in an online mode only. In case you require a hard copy of your course completion certificate, it will be courier to your communication address.
We provide 24/7 online support to resolve all your technical queries even after you have completed the course. Your access to our Technical Support is for a lifetime. Our support team will help you in resolving queries, during and after the course. You can raise a support ticket to our technical support from this page https://www.oxzeracademy.com/submit-ticket/
Yes, except for courses listed under academic category, you will get a certificate after you complete the course successfully.
You can find the course duration on the course details page.
Online course assignments depend largely on the course you have enrolled into. But in general, learners should expect assignments similar to those in-person programs. An assignment may require you to work either individually or in groups with other learners on a project. Depending on your course, you may also be required to prepare and give remote presentations.
Exams will be conducted online after all the modules in the course are completed. It is mandatory to switch on the camera while giving a Test or Exam and will be strictly monitored by the instructor. You should score at least 60% marks in the qualifying exam to complete the course successfully and receive your course certificate.
Before enrolling in an online course a learner should go through all the details regarding the course, prerequisite etc. for which they are enrolling and must read all terms and conditions of Oxzer Academy before enrolling in the course.
Yes, our placement team will assist you in all possible ways to find a right job if you are in need of the same. The final decision on hiring will always be based on your performance in the interview and the requirements of the recruiter. Moreover, Oxzer Academy courses are well recognised in the industry as it is a testament to the intensive and hands-on learning you have gone through and the real life use cases you have learned during the course.
Once you enrol to the course, the LMS access will be instantly provided to you and will be available for lifetime. You will be able to access the complete set of previous class recordings, PPTs, PDFs, assignments etc. Moreover the access to our 24x7 support team will be granted instantly as well.
Yes, the access to the course material will be available for lifetime once you have enrolled into the course.
You can read the complete set of Terms and Conditions for this program at https://www.oxzeracademy.com/terms-and-conditions/
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