Skill Development Programme in AI & ML
Our Skill Development course ‘Mastering AI: From Fundamentals to Generative Models’ is meticulously crafted to bridge the current market gap and anticipate future industry needs. Designed for beginners with no prior knowledge of AI, the course progresses from basic to advanced levels. Applicants with a keen interest in emerging technologies are eligible for the programme.
As a learner, you will be introduced to the fundamental and advanced tools and concepts essential for an AI Engineer. The course provides a comprehensive overview of the data, questions, and methodologies that AI Engineers work with. It is structured into two main components: a conceptual introduction that explains how to transform data into actionable insights, and a practical introduction to the tools you will use throughout the Program.
This course consists of beginner, intermediate and advanced levels totalling 300+ learning hours, after which you may consider embarking on a career as an AI Engineer. You will also have access to round-the-clock support, tutoring, and a variety of other support mechanisms. The course features real-time case studies and a live project to provide you with hands-on coding experience and decision-making skills.
Accreditation
Each of the skill development programmes are accredited by the London Management Qualifications Authority (LMQ).
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Descriptive & Inferential Statistics
In the Descriptive Inferential Statistics module, students will explore fundamental statistical concepts and techniques essential for data analysis in AI engineering.
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Statistical Analytics
The "Statistical Analytics" module delves into advanced statistical methods essential for building and evaluating predictive models in AI and data science.
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Applied Multivariate Analysis
The Applied Multivariate Analysis module provides students with the skills and knowledge to analyze and interpret complex datasets involving multiple variables. Beginning with fundamental concepts such as Measures of Central Tendency, Dispersion, and Association, students will understand how to summarize and describe multivariate data.
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Predictive Statistical Modelling
The Predictive Statistical Modelling module equips students with advanced techniques to create robust predictive models for diverse data scenarios in AI and data science.
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Time Series Forecasting
The Time Series Forecasting module provides students with comprehensive techniques to analyze and predict temporal data patterns essential for various applications in AI and data science.
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Natural Language Processing
The Natural Language Processing (NLP) module equips students with the skills to analyze, interpret, and generate human language using computational techniques.
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Deep Learning
The Deep Learning module provides students with a comprehensive understanding of advanced neural network techniques essential for AI and data science applications. The course begins with an introduction to the core concepts of deep learning, including the architecture and functioning of neural networks.
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LLM’s and Generative AI
The LLMs and Generative AI module immerses students in the cutting-edge techniques and models driving advancements in natural language processing and generative artificial intelligence.
Career Prospects
- Business Intelligence Analyst
- Research Scientist
- Data Analyst
- Operations Research Analyst
- Supply Chain Analyst
- Data Scientist
- Machine Learning Engineer
- AI Research Scientist
- Econometrician
- Computer Vision Engineer
- Chatbot Developer
- Financial Analyst
- Conversational AI Developer
- Environmental Scientist
- Robotics Engineer
