Course Overview:

Unlock the power of Artificial Intelligence (AI) with this comprehensive Machine Learning (ML) and Deep Learning (DL) course. Learn practical skills for data preparation, model building, and distributed training using Apache Spark. Master industry-standard tools and gain the expertise to design and implement AI solutions across various domains. 

After completing this course, participants will be able to

  • Explain core ML and DL concepts
  • Utilize open-source tools like Spark MLlib, TensorFlow, PyTorch
  • Preprocess and transform data for model training
  • Implement the Machine Learning lifecycle
  • Train and evaluate deep learning models
  • Design and deploy ML applications
  • Collaborate effectively with data science teams

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Key features of the course:

  • Hands-on, project-based learning

  • Industry-relevant curriculum

  • Expert instructor with real-world experience

  • Access to cutting-edge tools and technologies

  • Collaborative learning environment

  • Career advancement opportunities

  • Earn a course completion certificate

  • Lifetime access to course materials

Who can participate in the training?

  • Aspiring data scientists and ML engineers
  • Developers seeking to integrate AI into their projects
  • Professionals looking to enhance their AI knowledge
  • Anyone interested in leveraging AI for business advantage

What are the prerequisites for the training?

  • Basic understanding of Python programming
  • Familiarity with linear algebra and statistics
  • Fundamental knowledge of operating systems and computer networking

Why Choose CloudThat as Your Training Partner?

  • Experienced instructors with proven track records
  • Focus on practical skills and real-world applications
  • Comprehensive learning materials and resources
  • Career guidance and support
  • Active learning community
  • Flexible learning options (online/in-person)
  • Commitment to student success

Learning Objectives of the Course

  • Master data preparation techniques for ML/DL projects
  • Gain hands-on experience with popular ML algorithms
  • Build and deploy deep neural network models
  • Leverage Apache Spark for distributed deep learning
  • Develop the skills to design and implement ML applications
  • Enhance communication and collaboration with data science teams
  • Explore career opportunities in the booming AI field

Course Outline: Download Course Outline

In this module, you will explore and learn about Data preparation tasks - Data preprocessing /cleaning, Feature Engineering and how pyspark built-in capabilities can be used to accomplish these tasks.

In this module, you will learn about ML Types and Models along with evaluation parameters and machine learning life cycle stages.

In this module, you will learn about Neural networks, a beautiful biologically inspired programming paradigm which enables a computer to learn from observational data and Deep learning, a powerful set of techniques for learning in neural networks.

In this module, you will understand distributed deep learning and how training time is massively reduced by distributing training tasks over multiple CPUs and leveraging Spark capability for same.

Certification details:

  • Upon successful course completion, participants will receive a certificate of achievement from CloudThat.
  • This certificate validates your newly acquired skills and knowledge in Machine Learning and Deep Learning.
  • It can be a valuable asset when pursuing career opportunities in the AI field.

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Course ID: 20282

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FAQs for Machine Learning and Deep Learning Training

Machine Learning uses algorithms to identify patterns in data, whereas Deep Learning uses layered neural networks to process large datasets and perform more advanced AI tasks

Machine Learning and Deep Learning are used in healthcare, finance, retail, cybersecurity, recommendation systems, predictive analytics, computer vision, and intelligent automation

This training equips you with practical AI and data science skills that can help you contribute to Machine Learning projects and support AI-driven business initiatives.

This course is ideal for developers, software engineers, data professionals, AI enthusiasts, and technical teams looking to build practical AI and Machine Learning skills.

Machine Learning helps businesses automate processes, improve decision-making, enhance customer experiences, detect patterns, and generate insights from large volumes of data.

You'll gain skills in data analysis, model building, neural networks, AI concepts, and applying Machine Learning to real-world business challenges.

Machine Learning professionals commonly use Python, TensorFlow, PyTorch, Scikit-learn, and Jupyter Notebook to build and deploy AI models.

Machine Learning training equips teams with AI skills to improve productivity, automate workflows, and develop data-driven solutions for business growth

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