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Machine Learning Online Training

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    Hear it from our Graduate

    Have Cracked Their Dream Job in Top MNC Companies

    Online Machine Learning Course to Advance Your Career

    • Machine learning, an exciting area of artificial intelligence, enables computers to learn from data and enhance their performance without having to be explicitly programmed.
    • It refers to a set of algorithms and techniques that allow machines to spot patterns, make predictions, and draw useful insights from massive volumes of data.
    • Machine learning algorithms can find complicated linkages and trends that are beyond the human capacity to notice by utilizing statistical modeling and computer power.
    • Machine learning has transformed multiple sectors, propelling improvements in healthcare, banking, autonomous cars, and many other industries.
    • Machines continually modify their models through iterative learning and feedback loops, improving accuracy and flexibility over time.
    • Machine learning continues to advance as data availability expands dramatically and computer resources become more powerful.
    • Machine learning Certifications are also widely recognized, which can lead to work prospects both locally and internationally.
    • Classroom Batch Training
    • One To One Training
    • Online Training
    • Customized Training
    • Enroll Now

    Course Objectives

    • Enhanced Knowledge and Skills: Machine Learning certification programs provide in-depth knowledge and practical skills required to understand and implement ML algorithms and techniques.
    • Career Opportunities: The demand for professionals skilled in Machine Learning is skyrocketing across industries.
    • Enhanced information and abilities: Machine Learning certification programs give the in-depth information and practical abilities necessary to comprehend and use ML algorithms and approaches.

    Due to the increasing number of jobs in the machine learning field, familiarity with the topic is more important. It is the goal of machine learning, a subfield of AI, to develop algorithms and models that will enable computers to learn from data and make decisions automatically, without human intervention. It's capable of understanding and responding to spoken language, finding objects in photographs, identifying fraud, offering advice, and even controlling autonomous cars.

    • Healthcare: Machine learning algorithms can evaluate massive volumes of medical data to aid clinicians in making accurate diagnosis and recommending the most effective treatment approaches. It can also assist anticipate disease outbreaks and identify possible risk factors.
    • Retail and e-commerce: Machine learning algorithms offer tailored suggestions, consumer segmentation, demand forecasting, and inventory management. This technology assists organizations in optimizing their marketing efforts, increasing customer happiness, and increasing total sales.
    • Autonomous Vehicles: The development of self-driving automobiles is primarily reliant on machine learning algorithms. Machine learning algorithms can make real-time choices and react to changing road conditions by processing massive volumes of data from sensors and cameras.

    Enrolling in a Machine Learning course can be an incredibly valuable and strategic decision for a multitude of reasons. In today's data-driven world, Machine Learning is playing an increasingly pivotal role across industries, from healthcare and finance to marketing and technology.

    • Programming Skills: A solid foundation in programming is required for machine learning. Python is the most often used language in this field owing to its simplicity and the availability of famous packages such as TensorFlow and scikit-learn.
    • Mathematics and Statistics: Machine learning algorithms rely significantly on mathematical and statistical principles. Understanding concepts such as linear algebra, calculus, probability, and statistics is essential for constructing and analyzing machine learning models.
    • Data Preprocessing: Machine learning models require clean, organized data for training. Data preparation entails activities such as data cleansing, feature selection, normalization, and managing missing values.
    • Machine Learning Algorithms: Understanding multiple machine learning algorithms is necessary for selecting the best model for a particular task.
    • Improved decision-making
    • Automation and efficiency
    • Personalization
    • Fraud detection
    • Improved healthcare outcomes
    • Enhanced customer insights
    • Continuous improvement
    • Develop foundational Machine Learning understanding.
    • Introduce various algorithms and models.
    • Provide hands-on experience through projects.
    • Cover model optimization and ethical considerations.
    • Prepare learners for real-world applications.
    • Understanding of basic statistics and statistical concepts.
    • Familiarity with data analysis and manipulation techniques.
    • Knowledge of algorithms and data structures.
    • Experience in data visualization.
    • Curiosity and willingness to learn.

    What careers are available for this Machine Learning course?

    • Machine Learning Engineer
    • Data Scientist
    • AI Research Scientist
    • Computer Vision Engineer
    • NLP Engineer

    Yes, students do often get to work on projects that are useful in the real world. Depending on the basics of the course, projects could include anything from making websites to writing code for apps. Students get hands-on experience with relevant workplace technology and practices through projects. This helps them get ready for their next step in the field.

    Is the Machine Learning course remarkable??

    Absolutely, the Machine Learning course is undeniably remarkable. It empowers learners with a comprehensive understanding of essential concepts and practical skills in Machine Learning. Through hands-on projects and expert guidance, it bridges theory and application, ensuring graduates are well-prepared for real-world challenges.

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    Overview of Online Machine Learning Course

    Machine learning is a fast expanding topic of data science and IT. This branch of AI is concerned with teaching machines to recognize patterns and generalize information about the world without being given any instructions. To rephrase: machine learning enables computers to learn from data and gradually enhance their capabilities. This is accomplished by using statistical methods and computing algorithms to sift through mountains of data in search of patterns, trends, and linkages. The primary focus of machine learning is the creation of intelligent machines with the capacity for self-directed learning and improvement. The models learn to recognize patterns and correlations in this training data, which they subsequently use to draw inferences or judgments about novel data. Finance, healthcare, retail, and transportation are just some of the many fields that might benefit from machine learning.

     

     

    Additional Info

    Advantages of Machine Learning Certification Course:

    • Obtaining a machine learning certification might open up numerous doors for you as the need for qualified labor in this sector rises. The ability to demonstrate expert knowledge in one's field is a major selling point of machine learning diploma programs. It may help you stand out to potential employers and increase your earning potential.
    • Earning a degree in machine learning is also an excellent method to get practical knowledge and expertise in the field. The focus of these courses is on providing students with a comprehensive grounding in machine learning, statistical modeling, and data analysis. The ability to explore complex information, construct predictive models, and apply machine learning approaches to real-world issues may be honed via hands-on experience with coding and real-world projects. Your technical proficiency will rise and your preparedness for the challenges you'll encounter in the field will strengthen thanks to this hands-on experience.
    • Also, getting certified in machine learning can greatly improve your chances of getting a job. As more and more companies make decisions based on data, the demand for people who know how to use machine learning keeps going up. By getting a known license in this area, you can set yourself apart from other applicants and make it more likely that you will get a high-paying job. A license can also give you the chance to work on cutting-edge projects and team up with top experts in your area.

    Future technologies of Machine Learning:

    Deep Reinforcement Learning: The goal of deep reinforcement learning is to provide robots the ability to learn and make judgments in complicated settings with the help of a combination of deep learning and reinforcement learning. The development of fields like robots, driverless cars, and video games stands to benefit from this technology.

    Generative Adversarial Networks (GANs): Adversarial generative models There has been a lot of focus on GANs in the recent years. A generator and a discriminator, both neural networks, compete with one another to form these models. Images, videos, and translations from text to images are only some of the applications of GANs. It's possible that as GAN technology develops, the resulting products will be more lifelike and high-quality.

    Explainable AI (XAI): Explainable AI (XAI) is an area of AI research and development that aims to build machine learning models that can justify their predictions and actions. With the growing sophistication and sway of machine learning comes a greater need for its results to be both transparent and interpretable. It is possible that in the not-too-distant future, we will have the technological wherewithal to build AI systems with explanations for their actions.

    Federated Learning: Federated learning is a distributed machine learning technique in which numerous devices or nodes work together to train a single shared model in a decentralized fashion. Since information is kept locally and only model changes are sent, this technique is advantageous from a privacy standpoint. The potential for federated learning to improve privacy, security, and scalability in future large-scale machine learning systems is exciting.

    Quantum Machine Learning: Through exploiting quantum features to carry out calculations that are beyond the scope of conventional computers, quantum computing has the potential to radically alter the landscape of machine learning. The goal of quantum machine learning is to create algorithms that can take use of these quantum benefits, leading to enhanced optimization, quicker training, and the capacity to tackle difficult problems.

    Transfer Learning and Meta-Learning: With the help of meta-learning, models may use the information they've gleaned from one area of study to excel in another.Meta-learning is the process of creating models that can learn to learn, allowing them to pick up abilities that can be applied to novel tasks with just a little amount of initial input. More progress in these areas in the future might improve the efficiency and flexibility of machine learning models.


    Career scope for Machine Learning:

    The growing relevance and breadth of application of machine learning across sectors has resulted in a plethora of job openings in the field. The following are examples of possible jobs and careers in machine learning:

    Machine Learning Engineer: To develop, implement, and maintain machine learning systems is the job of a machine learning engineer. Algorithm design, data cleaning, model training, and rollout are all tasks they tackle. They usually have a deep understanding of machine learning libraries and frameworks, as well as a solid foundation in programming.

    Data Scientist: Data scientists are experts in sifting through large amounts of information using statistical and machine learning techniques to draw conclusions and identify trends. They do tasks related to analyzing data, developing features for models, and conducting predictive analytics. Scientists that work with data share their results with relevant parties and push for more data-driven decisions.

    Research Scientist: Algorithm innovation, model refinement, and theoretical advancement are all areas of focus for these experts. Scientists that specialize in research and development often find employment in universities or private companies.

    AI/ML Consultant: Consultants in artificial intelligence and machine learning help businesses make sense of the many available machine learning options. They analyze company requirements, create machine learning strategies, and provide assistance with model selection, creation, and incorporation. Consultants collaborate closely with their customers to enable the smooth integration of machine learning tools.

    AI/ML Product Manager: The role of the AI/ML product manager is to supervise the creation and distribution of AI/ML related goods and services. They collaborate with engineers, data scientists, and other stakeholders to determine the product's direction, rank its features in order of importance, and guarantee that it meets consumer demand. Managers of AI/ML products need expertise in both technology and business.


    Roles and Responsibilities of Machine Learning Engineer:

    • Engineers specializing in machine learning are essential to the creation and deployment of new machine learning models and algorithms. They create, implement, and maintain the infrastructure enabling computers to acquire knowledge and make choices based on that knowledge.
    • Identifying patterns and trends in huge datasets is a key responsibility of a Machine Learning engineer. Predictive models that may be applied to difficult issues are developed with the use of statistical methods and algorithms. These models are then used in new or existing systems or as stand-alone software.
    • Machine Learning engineers not only analyze and model data, but also choose the best methods and tools for the job. They should be well-versed in all the many types of machine learning, from supervised to unsupervised to reinforcement. Their job is to compare how well various algorithms function and then tweak those that perform the best.
    • Engineers in this field must also watch out for the stability and scalability of machine learning systems. They need to create dependable frameworks that can cope with heavy loads of data and user traffic. This necessitates the development of optimized algorithms and the establishment of streamlined data processing pipelines. They should also keep an eye on how well machine learning systems are doing in the real world so they can fine-tune them as needed.

    Tools used by Machine Learning professionals:

    There are libraries and tools to help with machine learning tasks including data preparation, model creation, and model assessment. Illustrations of machine learning applications:

    Python:

    Professionals in the field of machine learning often utilize the Python programming language. There are a number of data-handling libraries that may be used with it, including NumPy, pandas, scikit-learn, TensorFlow, PyTorch, Matplotlib, and Seaborn.

    scikit-learn:

    Popularity of the scikit-learn machine learning library written in Python. Dimension reduction, regression, classification, and clustering are all available. Resources for model selection, model assessment, and data preparation are provided.

    TensorFlow:

    Google's TensorFlow is a deep learning library. It simplifies the processes of creating and training deep neural networks. TensorFlow provides both the high-level Keras framework for quick model creation and the low-level APIs needed for fine-tuning.

    PyTorch:

    PyTorch, another well-liked deep learning application, facilitates the work of researchers and developers with its adaptable computational graph. It simplifies the process of training deep learning models by bridging the gap between Python and GPU acceleration.

    Keras:

    Keras is an application programming interface used in conjunction with TensorFlow or another backend library to construct and deploy neural networks. It provides a simple user interface for building and enhancing deep learning models. Keras allows for fast prototyping by supporting both convolutional and recurrent neural networks.

    Jupyter Notebook:

    The interactive coding environment Jupyter Notebook may be used as a front end for these tasks. It is frequently used during the data analysis, model building, and result display stages of machine learning and supports a wide range of computer languages, including Python.

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    Key Features

    ACTE Chennai offers Machine Learning Training in more than 27+ branches with expert trainers. Here are the key features,
    • 40 Hours Course Duration
    • 100% Job Oriented Training
    • Industry Expert Faculties
    • Free Demo Class Available
    • Completed 500+ Batches
    • Certification Guidance

    Authorized Partners

    ACTE TRAINING INSTITUTE PVT LTD is the unique Authorised Oracle Partner, Authorised Microsoft Partner, Authorised Pearson Vue Exam Center, Authorised PSI Exam Center, Authorised Partner Of AWS .

    Curriculum

    Syllabus of Machine Learning Online Training
    Module 1: Introduction to Machine Learning
    • Overview of Machine Learning
    • Types of Machine Learning algorithms
    • Applications of Machine Learning in various domains
    • Introduction to Python and popular ML libraries
    • NumPy, Pandas, and scikit-learn
    Module 2: Data Preprocessing and Exploration
    • Data cleaning and handling missing values
    • Data transformation techniques (scaling, normalization)
    • Feature selection and engineering
    • Exploratory Data Analysis (EDA) using visualizations
    Module 3: Supervised Learning Algorithms
    • Linear Regression
    • Logistic Regression
    • Decision Trees and Random Forests
    • Support Vector Machines (SVM)
    • Naive Bayes Classifier
    Module 4: Unsupervised Learning Algorithms
    • K-Means Clustering
    • Hierarchical Clustering
    • Principal Component Analysis (PCA)
    • Association Rule Learning (Apriori algorithm)
    • Anomaly detection
    Module 5: Model Evaluation and Validation
    • Training and testing datasets
    • Cross-validation techniques
    • Evaluation metrics (accuracy, precision, recall, F1-score)
    • Confusion matrix and ROC curves
    • Bias-Variance tradeoff
    Module 6: Ensemble Methods and Model Selection
    • Bagging and Random Forests
    • Boosting and AdaBoost
    • Stacking and Blending
    • Hyperparameter tuning
    • Model selection techniques
    Module 7: Deep Learning Fundamentals
    • Introduction to Neural Networks
    • Activation functions
    • Backpropagation and Gradient Descent
    • Convolutional Neural Networks (CNNs)
    • Recurrent Neural Networks (RNNs)
    Module 8: Deep Learning Applications
    • Image Classification
    • Object Detection and Localization
    • Natural Language Processing (NLP)
    • Sequence-to-Sequence Models
    • Generative Adversarial Networks (GANs)
    Module 9: Reinforcement Learning
    • Markov Decision Processes (MDPs)
    • Q-Learning and Value Iteration
    • Policy Gradient Methods
    • Deep Q-Networks (DQN)
    • Applications of Reinforcement Learning
    Module 10: Advanced Topics in Machine Learning
    • Transfer Learning
    • Explainable AI and Interpretability
    • Time Series Analysis
    • Autoencoders and Variational Autoencoders
    • Model Deployment and serving with cloud platforms
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    Need customized curriculum?

    Hands-on Real Time Machine Learning Projects

    Project 1
    Azure Security Center

    Enhance the security of Azure resources by implementing Azure Security Center.

    Project 2
    Hybrid Cloud Deployment

    Implement a hybrid cloud solution connecting on-premises infrastructure.

    Our Machine Learning Online Course to Advance Your Career

    The Machine Learning training courses offered by ACTE are designed to provide students the skills they need to succeed in the field of Machine Learning and to assist them in finding employment there.

    • Every student and professional who completes our classroom or online training will have the opportunity to be placed after completing our machine learning course with placement.
    • For placement, ACTE offers distinct student portals where students may access interview dates and other important details.
    • Reputable companies like HCL, Wipro, Dell, HP, Accenture, Google, CTS, TCS, IBM, and others have hired a large number of ACTE students.
    • Experts in machine learning help students create resumes that adhere to current industry requirements.
    • Mock exams and mock interviews are used to enhance candidates' knowledge and skills and get them ready for actual workplace situations.
    • The placement support team caters to the needs of candidates during the hiring process, providing the necessary assistance and guidance.

    Obtain Industry Recognized Machine Learning Certification

    ACTE provides industry-recognized Machine Learning Courses that will provide you with the skills that employers want. Receiving hands-on training in Machine Learning software and its functionality gives you a competitive advantage in the job market. The certificate you receive is significant because it validates your hands-on experience with real-world projects and sets you apart from other candidates. ACTE offers flexible study options as well as placement assistance, making it an ideal choice for students looking to excel in the field of Machine Learning. Enroll in a Machine Learning Course With Certificate right now to get started in the Machine Learning sectors.

    • Increased Job Opportunities
    • Higher Salary Potential
    • Enhanced Skillset
    • Credibility and Recognition
    • Networking Opportunities
    • Ability to preprocess and analyze data for machine learning.
    • Knowledge of evaluating and selecting the appropriate machine learning model.
    • Understanding of the importance of feature engineering and feature selection in machine learning.
    • Ability to apply machine learning techniques to real-world problems and datasets.
    • Familiarity with ethical considerations and bias in machine learning.

    Machine learning is a fast expanding area with several employment options. As technology advances, the demand for employees knowledgeable in machine learning will only grow. You may position yourself for lucrative work opportunities and a successful career by gaining knowledge and abilities in this industry.

    • Introduction to Machine Learning
    • Machine Learning Foundations
    • Python for Machine Learning
    • Supervised Learning
    • Unsupervised Learning
    • Deep Learning

    Obtaining a Machine Learning (ML) certification can enhance your employability and increase your chances of securing employment in the field of Machine Learning. If the job you are applying for specifically requires Machine Learning skills or a particular certification, having a relevant ML certification can be a valuable advantage.


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    Acquire Training From Our Expert Machine Learning Trainers

    • Our instructors are adept at demystifying difficult Machine learning principles so that learners may understand them.
    • Our Machine learning online training provides practical, hands-on instruction that enables students to gain first-hand experience with machine learning tools and services.
    • They are able to provide students useful advice and in-depth insights into real-world situations since they have in-depth understanding of machine learning's characteristics and capabilities.
    • Our machine learning instructors keep current on the most recent machine learning innovations and best practices, making sure that students receive the most pertinent and current training possible.
    • Machine learning trainers are skilled specialists with a focus on instructing and advising others.
    • Additionally, knowledgeable instructors might offer insightful advice that isn't often included in textbooks.

    Machine Learning Course FAQs

    Looking for better Discount Price?

    Call now: +9193833 99991 and know the exciting offers available for you!
    • ACTE is the Legend in offering placement to the students. Please visit our Placed Students List on our website
    • We have strong relationship with over 700+ Top MNCs like SAP, Oracle, Amazon, HCL, Wipro, Dell, Accenture, Google, CTS, TCS, IBM etc.
    • More than 3500+ students placed in last year in India & Globally
    • ACTE conducts development sessions including mock interviews, presentation skills to prepare students to face a challenging interview situation with ease.
    • 85% percent placement record
    • Our Placement Cell support you till you get placed in better MNC
    • Please Visit Your Student Portal | Here FREE Lifetime Online Student Portal help you to access the Job Openings, Study Materials, Videos, Recorded Section & Top MNC interview Questions
    ACTE
      • Gives
    Certificate
      • For Completing A Course
    • Certification is Accredited by all major Global Companies
    • ACTE is the unique Authorized Oracle Partner, Authorized Microsoft Partner, Authorized Pearson Vue Exam Center, Authorized PSI Exam Center, Authorized Partner Of AWS .
    • The entire Machine Learning training has been built around Real Time Implementation
    • You Get Hands-on Experience with Industry Projects, Hackathons & lab sessions which will help you to Build your Project Portfolio
    • GitHub repository and Showcase to Recruiters in Interviews & Get Placed
    All the instructors at ACTE are practitioners from the Industry with minimum 9-12 yrs of relevant IT experience. They are subject matter experts and are trained by ACTE for providing an awesome learning experience.
    No worries. ACTE assure that no one misses single lectures topics. We will reschedule the classes as per your convenience within the stipulated course duration with all such possibilities. If required you can even attend that topic with any other batches.
    We offer this course in “Class Room, One to One Training, Fast Track, Customized Training & Online Training” mode. Through this way you won’t mess anything in your real-life schedule.

    Why Should I Learn Machine Learning Course At ACTE?

    • Machine Learning Course in ACTE is designed & conducted by Machine Learning experts with 10+ years of experience in the Machine Learning domain
    • Only institution in India with the right blend of theory & practical sessions
    • In-depth Course coverage for 60+ Hours
    • More than 50,000+ students trust ACTE
    • Affordable fees keeping students and IT working professionals in mind
    • Course timings designed to suit working professionals and students
    • Interview tips and training
    • Resume building support
    • Real-time projects and case studies
    Yes We Provide Lifetime Access for Student’s Portal Study Materials, Videos & Top MNC Interview Question.
    You will receive ACTE globally recognized course completion certification Along with project experience, job support, and lifetime resources.
    We have been in the training field for close to a decade now. We set up our operations in the year 2009 by a group of IT veterans to offer world class IT training & we have trained over 50,000+ aspirants to well-employed IT professionals in various IT companies.
    We at ACTE believe in giving individual attention to students so that they will be in a position to clarify all the doubts that arise in complex and difficult topics. Therefore, we restrict the size of each Machine Learning batch to 5 or 6 members
    Our courseware is designed to give a hands-on approach to the students in Machine Learning. The course is made up of theoretical classes that teach the basics of each module followed by high-intensity practical sessions reflecting the current challenges and needs of the industry that will demand the students’ time and commitment.
    You can contact our support number at 93833 99991 / Directly can do by ACTE.in's E-commerce payment system Login or directly walk-in to one of the ACTE branches in India
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          Other Category Placements
          • Non-IT to IT (Career Transition) 2371+
          • Diploma Candidates3001+
          • Non-Engineering Students (Arts & Science)3419+
          • Engineering Students3571+
          • CTC Greater than 5 LPA4542+
          • Academic Percentage Less than 60%5583+
          • Career Break / Gap Students2588+

        Job Opportunities in Machine Learning

        More Than 35% of Individuals Favor Machine Learning. Machine Learning Stands Out as One of the Most Popular and Sought-After Technologies in the Tech Industry.

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