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Artificial Intelligence in - Developers

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Objectives

This course emphasizes hands-on implementation of AI into applications, covering APIs, pre-trained models, and AI frameworks. The focus is on building scalable, intelligent features, including NLP, computer vision, and generative AI. So that software solutions become more adaptive and capable of real-world problem-solving. It also underlines strategies for integrating AI responsibly, maintaining performance and security, while accelerating development cycles across web, mobile, and enterprise platforms.



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Course Outcome

Gain practical mastery of core AI and machine learning principles applied in software development.
Confidently build, train, and deploy machine learning models using popular frameworks like TensorFlow and PyTorch.
Integrate AI APIs and pre-trained services into applications for advanced NLP, computer vision, and generative AI capabilities.
Design and develop intelligent chatbots and AI-powered features tailored to real-world use cases.
Deploy scalable AI solutions on cloud or edge environments following best DevOps practices.
Implement ethical AI development ensuring transparency, fairness, and privacy compliance.
Deliver end-to-end AI-driven applications from prototype to production confidently.

Why Mazenet?


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    Expert Faculty

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

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    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.

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    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.

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    Learning Paths

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

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    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.

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    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.

Delivery Highlights

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    Customized Training Modules

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

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    Certification

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

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    Multi-language Support

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

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    Personalized Training Reports

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

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    Industry-Oriented Training

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

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    Diverse Training Platforms

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

Contact Us
Ready to get started?
Let's chat.
info@mazenetsolution.com +91 9500929297
          +91 7397723052
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Course Preview

  • Understand the role of AI in modern application development.
  • Explore how AI-driven logic differs from traditional programming approaches.
  • Review key AI concepts and their application in software projects.

  • Learn the fundamentals of machine learning using Python libraries.
  • Build and evaluate classification and regression models.
  • Use scikit-learn, pandas, and NumPy for practical ML implementations.

  • Get hands-on with popular ML frameworks like TensorFlow, Keras, and PyTorch.
  • Explore Hugging Face Transformers for natural language processing.
  • Discover LangChain for building applications with large language models (LLMs).

  • Working with Pre-Trained Models and APIs
  • Leverage ready-to-use AI services from OpenAI, Google Cloud, AWS, and Azure.
  • Utilize APIs for text generation, translation, summarization, and vision tasks.
  • Integrate speech-to-text and voice assistant features into applications.

  • Dive into the potential of large language models.
  • Learn prompt engineering and chaining techniques.
  • Develop intelligent chatbots and Retrieval-Augmented Generation (RAG) systems using
  • vector databases like FAISS and Pinecone.

  • Work on image classification, object detection, and segmentation.
  • Apply OpenCV and TensorFlow for real-time AI-powered image processing.
  • Explore use cases in medical imaging, face recognition, and quality control.

  • Practice tokenization, stemming, and lemmatization.
  • Conduct sentiment analysis, keyword extraction, and text classification.
  • Use tools such as spaCy, Hugging Face, and NLTK for complex NLP tasks.

  • Learn to deploy models using Flask and FastAPI.
  • Create Docker containers and build user interfaces with Streamlit or Gradio.
  • Host AI models on cloud platforms like AWS Sagemaker and Azure ML.

  • Understand the importance of fairness, transparency, and responsible AI practices.
  • Understand the importance of fairness, transparency, and responsible AI practices.
  • Handle data carefully and apply ethical labeling standards.
  • Ensure compliance with regulations such as GDPR and CCPA.

  • Build a full-stack chatbot using OpenAI API.
  • Develop an image classifier with custom training.
  • Deploy a predictive model using FastAPI and Docker.
  • Implement an LLM-based document summarizer using LangChain.