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Artificial Intelligence in - Data Analytics

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Objectives

This course focuses on how AI enhances traditional analytics by uncovering deep insights, automating data processing, and enabling predictive and prescriptive modeling. It emphasizes the practical integration of machine learning, NLP, and generative AI to transform raw data into actionable, decision-driving intelligence. The program also highlights how AI-powered visualization and real-time analytics can reveal trends and anomalies that might otherwise go unnoticed, empowering organizations to make faster and more confident decisions.



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Course Outcome

Master integrating AI into data analytics workflows to automate data processing and extract deeper insights.
Confidently build, validate, and deploy machine learning models for accurate predictive analytics and trend forecasting.
Apply advanced natural language processing techniques to analyze unstructured data and generate business insights.
Design AI-powered visualizations and real-time dashboards that simplify complex data for effective decision-making.
Leverage generative AI tools to automate reporting, documentation, and insight generation organizationally.
Make impactful, data-driven business recommendations using prescriptive analytics and scenario modeling.
Ensure ethical AI use emphasizing bias elimination, explainability, and compliance with data privacy laws.
Translate complex business problems into AI-driven analytical solutions that deliver measurable value.

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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Get Started Today

Course Preview

  • Explore how analytics evolved from traditional BI dashboards to AI-powered insights.
  • Understand key AI technologies like ML, NLP, and Deep Learning.
  • See how AI enhances descriptive, predictive, and prescriptive analytics.
  • Learn from real-world business use cases across multiple domains.

  • Clean messy data with AI-based anomaly detection and smart imputation.
  • Experiment with automated feature engineering to improve models.
  • Discover enrichment techniques with external AI sources and APIs.
  • Work hands-on with tools like Pandas Profiling, AutoML, and D-Tale.

  • Build supervised and unsupervised learning models.
  • Apply classification and regression algorithms for business predictions.
  • Explore time-series forecasting to predict future trends.
  • Practice using scikit-learn, XGBoost, and Prophet.

  • Extract valuable insights from emails, reviews, and unstructured documents.
  • Perform sentiment analysis, topic modeling, and intent detection.
  • Apply keyword tagging to make text data actionable.
  • Work with tools like spaCy, NLTK, and LLM-based summarizers.

  • Design AI-driven dashboards that suggest insights automatically.
  • Ask questions in plain language and get data answers instantly.
  • Highlight anomalies and trends with built-in AI visuals.
  • Try out Power BI, Tableau, and Qlik Sense with AI features.

  • Understand real-time processing of continuous data streams.
  • Explore AI-driven fraud alerts, IoT sensor monitoring, and social media analysis.
  • Build live dashboards using Kafka and Azure Stream Analytics.

  • Use LLMs to auto-generate reports and summaries.
  • Automate documentation and deliver insights faster.
  • Learn prompt engineering for effective business queries.

  • Apply decision trees and optimization techniques.
  • Run “what-if” scenarios with prescriptive analytics.
  • See recommendation systems in action across HR, finance, and sales.

  • Ensure fairness and transparency in AI-driven models.
  • Understand global standards like GDPR and HIPAA.
  • Build interpretable pipelines with responsible AI practices.

  • Work hands-on with a churn prediction model.
  • Create live anomaly detection dashboards.
  • Apply sentiment analysis to customer reviews.
  • Experiment with AutoML for forecasting.