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Generative AI For Data Scientists Training Online

Generative AI For Data Scientists Online Course - Students will learn with real time examples, online practices to earn Generative AI For Data Scientists certification online” from the list of professional Instructors in USA. Below listed trainers provides learners training material, course curriculum, self-study videos, free demo, exam prep questions, e-books & more. All the Generative AI For Data Scientists online tutorial classes have exclusive lectures and comprehensive sessions on lessons to turn you as expert.

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Key Highlights

  • Live or virtual instructor-led classes
  • Quality course material provided
  • Become a certified expert on the subject
  • Instant access to reference material
  • Get high-pay jobs offers post-training

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      Generative AI For Data Scientists

      IT Tutor PRO in Burlington, MA provides instructor led live Online Generative AI For Data Scientists training with real time scenario, e-books, self-directed education programs , also facilities such as Placement
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      Generative AI For Data Scientists

      The next class is running  Jun 9 2025
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      Upcoming Instructor-Led Generative AI For Data Scientists live online training dates

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      • Jun 9 2025 Jul 9 2025
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      • Jun 10 2025 Jul 10 2025
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      • Jun 12 2025 Jul 12 2025
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      • Jun 13 2025 Jul 13 2025
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      FAQ's on Generative AI For Data Scientists training & certification

      • What is the average salary of a Gen AI Data Scientist in the USA?

        The average salary of a Generative AI Data Scientist in the USA ranges between $120,000 and $160,000 per year, depending on factors like experience, location, and expertise in tools and technologies such as GPT-3.5 and GANs.

      • What are the common Generative AI Data Scientist job prospects in the USA?

        Generative AI Data Scientists in the USA have opportunities in technology, healthcare, finance, e-commerce, and entertainment industries. Common roles include AI Research Scientist, Machine Learning Engineer, Data Scientist with LLM expertise, and Generative AI Specialist focusing on data visualization and feature engineering.

      • Is generative AI useful in data science?

        Yes, generative AI revolutionizes data science by enabling data generation, automated exploratory data analysis (EDA), feature engineering, and enhanced data visualizations. It accelerates workflows, uncovers complex patterns, and generates actionable insights, making data analysis more efficient and insightful.

      • How do I become an AI Data Scientist?

        To become an AI Data Scientist, you need to:

        1. Gain foundational knowledge in data science, machine learning, and programming (e.g., Python).

        2. Learn advanced AI concepts like Generative AI and prompt engineering.

        3. Develop hands-on experience with tools like GPT-3.5 and TensorFlow.

        4. Join a certification course, such as those offered by Sulekha, which partners with top industry-recognized course providers to provide high-quality training and resources.

      • Is data science still in demand in 2024?

        Data science remains in high demand in 2024 due to the growing need for data-driven decision-making across industries. The integration of generative AI has further expanded the field’s potential, making roles like Data Scientist and AI Specialist more relevant than ever.

      • How is generative AI used in data science?

        Generative AI is used in data science for:

        • Data augmentation and generation to create synthetic datasets.

        • Automated exploratory data analysis (EDA) for faster insights.

        • Feature engineering to improve model performance.

        • Data visualization with AI-generated insights for enhanced storytelling.

        • Querying databases and automating repetitive tasks in data pipelines.

      • Can you list out a few Generative AI tools for data science?

        Here are a few generative AI tools for data science:

        1. GPT-3.5 for generating text-based insights and data augmentation.

        2. ChatCSV for querying and analyzing structured data.

        3. Tomat.ai for AI-driven decision-making support.

        4. TensorFlow for building custom generative models.

        5. PyTorch is used to implement GANs and large language models.

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