| Attribute | Detail |
|---|---|
| Format | Online (e-LMS) |
| Level | Intermediate |
| Duration | 6 Weeks |
| Certification | e-Certification + e-Marksheet |
| Fee | ₹8249 / $103 |
| Tools | Python TensorFlow PyTorch Keras Scikit-learn Jupyter Notebook Google Colab Hugging Face |
About the Data Science and AI for Beginners Course
The Data Science and AI for Beginners course introduces key concepts of data science and artificial intelligence, perfect for those just starting out. Over 6 weeks, you'll learn how to handle data, understand machine learning basics, and use industry-standard AI tools.
With no prior experience required, this program gives participants hands-on experience, ensuring a strong foundation in AI and data analysis. By the end of this course, you’ll know how to work with data, apply AI techniques, and make informed, data-driven decisions.
Program Highlights
• Comprehensive coverage of Data Science and AI for Beginners from fundamentals to advanced applications
• Hands-on projects and real-world case studies in Artificial Intelligence
• Expert-curated curriculum aligned with current industry standards
• Access to recorded lectures and e-LMS platform for flexible, self-paced learning
• e-Certification and e-Marksheet upon successful completion
• Dedicated mentor support and interactive doubt-clearing sessions
• Exposure to industry-standard tools and platforms used in Artificial Intelligence
• Career-oriented training for academic and professional growth in Artificial Intelligence
Course Curriculum
Module 1: Introduction to Data Science (2 Weeks)
- Overview of data science and its role in AI
- Key techniques in data collection, cleaning, and analysis
- Structured vs. unstructured data explained
- Introduction to Python for data handling
Module 2: Fundamentals of Machine Learning (2 Weeks)
- Supervised vs. unsupervised learning
- Key algorithms: Decision Trees, K-Nearest Neighbors, Linear Regression
- Using Scikit-learn to build machine learning models
- Evaluating model performance: metrics and error measurement
Module 3: Core AI Tools – Pandas, NumPy, and Matplotlib (2 Weeks)
- Using Pandas for data manipulation
- NumPy for numerical computing and arrays
- Data visualization with Matplotlib: charts, graphs, and plots
- Hands-on project: Create a visual data report for business insights
Tools, Techniques, or Platforms Covered
Python TensorFlow PyTorch Keras Scikit-learn Jupyter Notebook Google Colab Hugging Face
Real-World Applications
- Apply Data Science and AI for Beginners skills directly to academic research, thesis work, and publications
- Build a professional portfolio showcasing practical Artificial Intelligence competencies
- Solve industry-relevant problems using Data Science and AI for Beginners methodologies and tools
- Contribute to open-source projects and collaborative research in Artificial Intelligence
- Prepare for competitive examinations, interviews, and professional certifications in Artificial Intelligence
Who Should Attend & Prerequisites
- Students pursuing degrees in Artificial Intelligence, science, engineering, or related disciplines
- Working professionals seeking to upskill or transition into Artificial Intelligence roles
- Researchers and academicians looking to adopt modern techniques in Artificial Intelligence
- Entrepreneurs, freelancers, and self-learners interested in practical Artificial Intelligence knowledge
Certification
