AI IN DATA ANALYTICS - Qtech-Sol offers Clinical Research / Trials, Pharmacovigilance, Drug Safety, Clinical Data Management, Clinical SAS Programming and Healthcare BA Training Programs
Category:
Analytics and Reporting
 
Duration:
4 Weeks / 100 Hours
 
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AI in Data Analytics

Introduction – AI in Data Analytics

Artificial Intelligence (AI) is revolutionizing the way data is processed, analyzed, and interpreted across industries — and healthcare and clinical research are no exception. From predictive modeling and natural language processing (NLP) to automation of routine analytics, AI is enabling faster insights and better decision-making.
The AIDA program introduces learners to the applications of AI in data analytics, combining fundamental AI concepts with real-world use cases in clinical research, life sciences, and business data environments. This course is designed for professionals seeking to bridge the gap between traditional data analytics and AI-driven approaches.

Course Name :  AI in Data Analytics
Course Code :  AIDA
Experience Level :  Intermediate
Qualification :  Bachelor’s / Master’s in Life Sciences, Statistics, Data Science, Computer Science, or related fields
Student Category :  : Data Analysts, SAS Programmers, Clinical Data Managers, AI/ML Enthusiasts, Career Changers into Data Analytics

Delivery Type

SIP – Self-Paced Online with Support

Duration & Delivery
  1. Course Duration: 4 weeks (100 hours)
  2. Format: Self-Paced Online with Support (narrated lessons, readings, quizzes, and role-based tasks).
Key Learning Objectives

   By completing this program, learners will:

  2. Understand the role of AI in modern data analytics.
  3. Learn how machine learning, NLP, and predictive algorithms enhance analytics.
  4. Explore AI applications in healthcare, pharma, and clinical research.
  5. Gain exposure to data cleaning, transformation, and feature engineering with AI tools.
  6. Understand automation in reporting, dashboards, and visualization.
  7. Explore AI-driven tools (Python, SAS Viya, R, cloud-based platforms).
  8. Review real-world case studies in predictive safety, clinical trials, and business analytics.
Who Should Take This Course
  1. Data Analysts seeking AI-driven skills.
  2. SAS Programmers / Statisticians expanding into AI/ML.
  3. Clinical Data Managers / PV professionals integrating AI into safety analytics.
  4. Healthcare professionals interested in AI for data insights.
  5. Career changers moving into AI and data science roles.
Benefits & Outcomes
  1. Build practical AI analytics skills applicable across industries.
  2. Gain readiness for roles at the intersection of AI, data science, and healthcare analytics.
  3. Learn to automate data cleaning, reporting, and visualization.
  4. Strengthen employability for roles such as AI Data Analyst, Clinical Data Scientist, or Healthcare Analytics Specialist.
Career Pathways: After completing this course.
  1. AI Data Analyst
  2. Clinical Data Scientist
  3. Healthcare Analytics Specialist
  4. Data Engineer (AI-focused)
  5. Business Intelligence Analyst (AI-driven)

Curriculum & Modules

Modules
1. Introduction to AI & Machine Learning in Data Analytics

2. Data Preparation, Cleaning & Transformation with AI Tools

3. Supervised & Unsupervised Learning Models for Analytics

4. AI in Predictive Modeling & Forecasting

5. Natural Language Processing (NLP) for Text Mining & Case Narratives

6. AI in Clinical & Safety Data Analytics (Signal Detection, PV Reporting)

7. Automation in Reporting, Dashboards & Visualization

8. AI Tools & Platforms (Python, R, SAS Viya, Cloud ML)

9. Ethical & Regulatory Considerations in AI Analytics

10. Case Studies – AI in Pharma, Healthcare, and Business Analytics
Getting in Touch:

For more information, please call us at +91 8925971788 / +91 8977943100 (WhatsApp)or email qpdc@qtechelearncenter.com. Our course specialists will reach out to you promptly to assist you in taking the next steps toward your career goals.