Advanced AI with IBM Machine Learning Certification

Course Overview:

The Advanced AI course equips students with essential Data Science skills. It consists of five modules: Python programming, data science fundamentals, Machine Learning, SQL, and deep learning with Gen AI basics. Students gain hands-on experience through real-world projects, solving complex data problems with various tools and techniques. The course includes all content from the IBM Machine Learning Professional Certificate, offering additional depth. We also prepare you for the IBM certification, ensuring you have the skills and confidence to succeed.

Module 1: Python Programming

In this module, students will delve into the fundamentals of Python programming language, including object-oriented programming (OOP) concepts and regular expressions, and their application in data science.

Module 2: Data Science Fundamentals

This module focuses on the core concepts and techniques in data science. Students will learn about data preprocessing, exploratory data analysis, feature engineering, and data visualization. They will also gain an understanding of statistical concepts and learn how to apply them in data science projects. By the end of this module, students will be equipped with the necessary skills to extract insights from data and communicate their findings effectively.

Module 3: Machine Learning

 In this module, students will dive into the exciting world of machine learning. They will learn various supervised and unsupervised machine learning algorithms, including linear regression, logistic regression, decision trees, random forests, and clustering techniques. Students will gain hands-on experience by building and evaluating machine learning models on real datasets. By the end of this module, students will have a solid understanding of machine learning algorithms and their application in solving real-world problems.

Module 4: SQL

This module focuses on Structured Query Language (SQL) and its role in data manipulation and analysis. Students will learn how to retrieve and manipulate data from relational databases using SQL queries. They will gain practical skills in database management, data extraction, and data manipulation. By the end of this module, students will be proficient in SQL and will be able to leverage its power to analyze and extract valuable insights from large datasets.

Module 5: Introduction to Deep Learning

In this module, we’ll explore powerful neural networks capable of solving complex problems. In this module, students will dive deep into the world of deep learning, learning about neural network architectures and their applications in solving real-world challenges.

Module 6: Introduction to Generative AI

In this module, students will gain a comprehensive understanding of generative models, particularly Large Language Models (LLMs), and their applications in text and image generation. Topics include the fundamentals and history of LLMs and NLP, transformer models, and practical skills using HuggingFace. Students will explore prompt engineering and fine-tuning techniques, including Quantized Low-Rank Adaptation (QLoRA) and Supervised Fine-Tuning (SFT). The module also covers evaluating fine-tuned models using metrics like GLUE, BLEU, ROGUE, and perplexity. By the end, students will be equipped to apply generative models in real-world scenarios, demonstrating their transformative impact across industries.

Attendance, Assignments, and Tests

• Attendance: 80% attendance is compulsory to be eligible for the placement program. This includes 3 hours a day at the office and 3 hours of work from home, 5 days a week.
• Assignments: All assignments should be completed on time and signed off by a mentor.
• Tests: You will have a test after every module that you need to clear. After completing all module tests, there will be a certification program test that you must pass to be eligible for the placement program.

After Completion, You Will Be Able to:

• Extract and transform data from various sources to prepare it for analysis.
• Develop and implement machine learning and AI algorithms to solve complex data problems.
• Create and optimize data models for efficient data processing and analysis.
• Design and deliver meaningful data visualizations to communicate insights effectively.
• Deploy and configure data solutions for real-world applications.
• Enable self-service analytics for stakeholders by providing user-friendly tools and resources.

As a proficient AI and machine learning specialist, you will work closely with business stakeholders to identify business requirements. You will collaborate with enterprise data analysts and data engineers to identify and acquire data. You will use AI, machine learning, and generative AI techniques to:

• Perform advanced data analysis to uncover hidden patterns and insights.
• Utilize machine learning models for predictive analytics.
• Implement AI-driven solutions to enhance business processes.
• Develop generative AI models for innovative applications.

Certification Preparation

We will help you prepare for the IBM Machine Learning Professional Certificate. After completing the course, you will have to appear for the exam. We will cover all the content required for this certification exam and assist you in your preparation to ensure you are well-equipped to succeed.

Placement Assistance

We will provide 100% placement assistance, helping you prepare your resume and build a strong GitHub profile. Additionally, we will assist you with optimizing your LinkedIn profile and job hunting strategies. We have tie-ups with various companies and will strive to arrange interview calls for you, ensuring you are well-prepared to secure a job in the data science field.