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In-depth Artificial Intelligence training
to automate business process

Objectives

Artificial Intelligence training in Mazenet is comprehensive with futuristic objectives to keep in pace with the fast technological advancements of the IT industry. Artificial Intelligence training is provided along with TensorFlow, Python and Mahout.

Artificial Intelligence with TensorFlow training includes neural networks (CNN), Perceptron in CNN, TensorFlow, TensorFlow code, transfer learning, graph visualization, recurrent neural networks (RNN), Deep Learning libraries, GPU in Deep Learning, Keras and TFLearn APIs, backpropagation, and hyperparameters via hands-on projects.

Natural language processing is covered under artificial intelligence training with python along with deep learning and reinforcement learning. Popular machine learning techniques, like classifications, recommendations and clustering are implemented through Mahout artificial intelligence training. The course can get anyone started on automation, data analysis, and robotics with artificial intelligence.

The course modules are structured to give an empirical value and understanding to the candidates. However, all course modules are highly customizable and can be structured to suit the requirements of your organization.

Course Outcome

Representation, problem solving, and learning methods of Artificial Intelligence.
Develop intelligent systems by assembling solutions to complex computational problems.
Assess the applicability, strengths, and weaknesses of representation, problem solving, and learning methods in solving particular engineering problems.
Understand the role of knowledge representation, problem solving and learning in intelligent-system engineering.
Understand the correlation between Manual and Automation Testing in real uses.
Learn Data-driven, Hybrid, and other frameworks.

Why Mazenet?



  • Expert Faculty

    Our Faculty comprises of 300+ SMEs with many years of experience. All our trainers possess a minimum of 8+ years of experience.

  • Proven Track Record

    We have served over 200+ global corporate clients, consistently maintaining a 99% success rate in meeting training objectives for 300+ technologies with quick turnaround time.

  • Blended Learning

    We provide course content over any platform that our clients prefer. You can choose an exclusive platform or a combination of ILT, VILT, and DLP.

  • Learning Paths

    The learning paths are very defined with clear benchmarks. Quantitative assessments at regular intervals measure the success of the learning program.

  • Case Study

    We have amassed over 10,000 case studies to support training delivery. Candidates will be trained to work on any real-time business vertical immediately after the training.

  • 24*7 Global Availability

    We are equipped to conduct training on any day, date or time. We have delivered training pan India, Singapore, North America, Hong Kong, Egypt and Australia.

Key Features

  • Customized Training Modules

    Training programs are highly flexible with module customizations to suit the requirements of the business units.

  • Certification

    The training can be supplemented with appropriate certifications that are recognized across the industry.

  • Multi-language Support

    Course content can be delivered in English, Spanish, Japanese, Korean or any other language upon request.

  • Personalized Training Reports

    Candidates are assessed individually at regular intervals and are provided unique learning suggestions to suit their learning calibre.

  • Industry-Oriented Training

    Industry-oriented training, completing which, candidates can be immediately deployed for billable projects.

  • Diverse Training Platforms

    Choose from Instructor-Led Training, Virtual Instructor-Led Training, Digital Learning Platform and Blended Training platforms

Course Preview

  • Decoding Artificial Intelligence
  • Fundamentals of Machine Learning & Deep Learning

  • Python functions, packages and routines
  • Pandas, NumPy, Matplotlib, Seaborn

  • K-NN classification
  • Multiple variable linear regression
  • Ensemble Techniques
  • Featurization, model selection & tuning

  • Introduction to Perceptron & neutral networks
  • Tensor Flow & Keras for Neural Networks & Deep Learning