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Program Overview
It will take some time for every one of the schools and universities to become familiar to the elements of Machine Learning (ML). It is very obvious that a total execution of such advancements in the schooling area requires a load of work. So, acquiring a machine learning certification course can be a bonus.
Machine learning, ML as its title defines, is involved as a process to make the machine run a task automatically. Discussing deep learning, it is a process to train machine for operating logically according to conditions only like a human mind. Artificial Intelligence relates to the Engineering and Science of advancing intelligent machines that can run and respond like human brains.
ML is a sub-division of artificial intelligence. The technology involves algorithms that can make conclusions and predictions based on huge data sets. The number of university and college students attending classes and online keeps on rising. The online and classroom learning at Kodetree is getting more prevailing with the help of technologies and tools used in this institution.
Elligibility
As such no criteria are required, but you have to pass at least graduation for the machine learning course.
Knowledge of Robotic Process Automation
Finance, health, and manufacturing industries are using ML to organize robotic process automation where intelligent drones and robots make the task simpler.
Improved IT Operations
It helps IT operations teams to capture, purify data, to obtain the root cause of troubles, and make intelligent business insights to make the company's triumph.
Transparency in Decision-Making
ML with the help of prophetic models brings clearness in decision-making in the field of retail, medicine, healthcare, and logistics.
Machine Learning Program Fee
If you take an in-person program at a Kodetree provider’s computer lab, we make available to you with the hardware and software for training. On the other hand, any travel expenses connected with in-person learning are yours but if you work for a company after completing the course that reimburses you for outside training. Depending on your current job, you may have to take off work to be present at training.
Course Curriculum
Get the perfect sense of balance of theory and practice.
Demo
Trial right to use
Projects
Real Projects
Homework
Assignment Work
Advice
Expert Guidance
Machine Learning Syllabus
With a program with leading experts, the course will help you to get the complex machine learning methods and make long term predictions for your first project.
Introduction to Python/R for Machine Learning: Basic syntax, data structures, Control flow, functions, and libraries. Mathematics for Machine Learning, Mathematical foundations of machine learning, Linear algebra (vectors, matrices, linear transformations), Calculus (differentiation, integration, and optimization)
Supervised Learning: linear regression, logistic regression, Decision trees, support vector machines. Unsupervised Learning: clustering (k-means, hierarchical clustering), Dimensionality reduction (PCA, t-SNE), Anomaly detection, Reinforcement Learning, Q-learning, Policy gradients
Popular libraries and frameworks, Machine learning algorithms, such as TensorFlow, Keras, aorch. Data Visualization Tools: Matplotlib and Seaborn. Convolutional neural networks (CNNs) for image processing, Recurrent neural networks (RNNs) for sequential data, Transformers for natural language processing.
Text preprocessing, Llanguage modeling, Machine translation, Computer Vision, Image classification, Object detection, Image segmentation, and 3D visio. Time Series Analysis, Forecasting, Anomaly detection, Seasonality analysis
Visualize vector representations of word embeddings Distinguish encoding from embedding., Describe contextual embedding, Large Language Models, Different types of language models and their components., The importance of context and parameters. Identify how large language models take advantage of self-attention.
Appreciate the breadth of components in a production ML system. Test your machine learning deployment and ask the right questions about your production ML system.
Learn from Top Academicians & Industry Experts
He can teach chatbots, virtual assistants and other tech sources to work together in a human-like manner. He has a wide experience in the healthcare and finance to customer service and education industry. He can train the students with the fine-tune ML models
Admission Process
Step 1
Sign up in a program
Step 2
Learn through guided courses
Step 3
Obtain the placement assistance
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Frequently Ask Questions
Machine Learning is a branch of AI where the machine learns to process the data from big data sets that are fed in the machine or software to discover and store them. These data sets are referenced by the machine to process and come back with future questions.
In Kodetree, the following skills are given to our students:
Deep perceptive of fundamental statistics / mathematics, good data modeling skills
Deep business domain data, good business analytics skills, good general idea of technical challenges and planned problem-solving skills
Good engineering skills, deep perceptive of cloud technologies, good system architecture
There is a part of the business society that can latch on to the most new trends in research. That part of the business community will take on ‘new’ things like ML. ML is a type of Artificial Intelligence, and principally means that the machine ‘learns without being taught’ as it has different statistical and algorithmic ‘facts.’ ML is currently pricey (requires the procure of specialized software or internet services, takes time and lots of effort to set up), but Kodetree can help to learn this field in a simpler way. Yes, learning ML is going to help your career. But to be helpful, you’ll need to do more than just understand what it is. Do some projects using ML.
The gains of Machine Learning are as follows,
It can simply distinguish the trends and patterns
It can learn and recover the predictions on its own and no human connection is required
It constantly improves the accurateness and efficiency
It can serve a lot of users with wide-ranging applications.
After learning the basics of machine learning, there are numerous advanced topics and areas of specialization that one can follow. Here are a few key areas to consider:
Deep Learning
Natural Language Processing (NLP)
Reinforcement Learning
Computer Vision
Model Deployment and Productionization
Ethics and Fairness in AI
Advanced Algorithms and Techniques
Big Data Technologies
MLOps
Research and Development
Completing a course on machine learning from Kodetree can open up several career options:
Machine learning engineer
Data scientist
Data analyst
Business intelligence analyst
AI research scientist
Computer vision engineer
Natural language processing (NLP) engineer
Robotics engineer
Software engineer
Big data analyst
Yes, there is 100% job placement at our institution as we have a tie-up with many MNCs.