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Key Highlights
In-Depth Curriculum: Engage with a rigorous curriculum that covers advanced machine learning algorithms, deep learning techniques, and state-of-the-art large language models (LLMs) such as GPT-4. The course also includes detailed modules on prompt engineering for optimizing AI responses and sophisticated methods in automatic data analytics, including predictive modeling and data-driven decision making.
Live Code-Along Sessions: Participate in live coding sessions where instructors demonstrate complex AI models and data analytics techniques in real time. These sessions emphasize practical implementation using Python, TensorFlow, PyTorch, and other industry-standard tools, allowing you to follow along and apply the concepts immediately.
Industry-Experienced Instructors: Learn from AI specialists and data scientists who have significant industry experience. Our instructors have contributed to notable AI projects and bring practical knowledge of deploying machine learning models, fine-tuning LLMs, and leveraging data analytics in enterprise environments.
Capstone Projects and Real-World Applications: Work on capstone projects that mimic real-world scenarios and business challenges. These projects involve building and deploying AI models, optimizing LLMs for specific tasks, and creating automated data analytics pipelines. By the end of the course, you will have a portfolio demonstrating your ability to solve complex problems using AI and data analytics.
Advanced Tools and Technologies: Gain hands-on experience with advanced AI and data analytics tools and platforms. The course includes training on cloud-based AI services (such as AWS SageMaker, Google AI Platform, and Azure Machine Learning), data visualization tools (like Tableau and Power BI), and collaborative environments (such as Jupyter Notebooks and GitHub).
Introduction
Many people are worried about the implications of generative AI tools such as Chat GPT.
How will AI affect senior professionals? Have you thought about this question?
Here’s our take.
AI still needs humans to run and operate it. If we use it right, it can increase our efficiency by 10x, but it cannot do work by itself.
This means that those who learn how to use AI will have a massive advantage over those who do not use AI to do better at their jobs.
And this includes senior professionals.
If you want to grow to the next level, it will be important to embrace and use AI to our advantage, rather than being amongst those who are phased out by it.
Learning how to use AI could also be your unfair advantage that enables you to stay relevant in the changing times, and have another feather on your cap.
The goal of this program is to enable you to use AI as a co-pilot for all your professional work, especially your brand building, drastically improve your productivity, effectiveness, and regularly play “out of your league” and generate surprisingly good results, on a consistent basis.
Who should take this course
- Professionals who want to deepen their understanding of AI and machine learning techniques, enhance their data analytics skills, and learn how to implement and optimize large language models for more effective data-driven solutions.
- Individuals with a background in software development looking to transition into AI and machine learning roles. This course provides the necessary knowledge to build, deploy, and maintain AI models and automated analytics systems.
- Those passionate about AI and its applications, including academic researchers and hobbyists, who wish to gain a structured and comprehensive understanding of current AI technologies and their practical implementations.
- Experts in business intelligence and data-driven decision-making who want to leverage AI and advanced analytics to gain deeper insights, automate processes, and improve strategic outcomes for their organizations.
- Recent graduates and students in fields related to computer science, engineering, mathematics, or statistics who are looking to specialize in AI and data analytics, preparing themselves for a career in one of the most dynamic and in-demand areas of technology.
Money-back guarantee
If you take this course, follow it diligently for a month, do all the exercises but still do not find value in it, or not able to understand or follow it or not find it good for any reason, we will refund the entire course fee to you. It is a 100% money-back guarantee with only one condition, you must pursue it properly for a month. If you don’t find it valuable after that, get your entire money back.
Training Methodology
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Online 24/7 access
Access to basic study material through an online learning management system, Android and iOS app
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Hard Copy Study Material
Hard copy study material modules to be couriered to your address
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Practical Exercises
2 practical exercises every week, followed by written feedback. There will be in class exercises, take home exercises, chapter wise MCQs and even some individual capstone projects
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Live Online Classes
Based on the exercises, there will be a live video-based online class. You can ask questions, share your screen, get personal feedback in this class.
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Convenient Class timings
Classes are held after regular work hours. Typically classes are kept on Sunday afternoon or 8-9 pm on other days.
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Live Doubt Clearing
You can ask questions, get your doubt cleared live as well as through online forums
Syllabus
Introduction to Artificial Intelligence ![](https://skillarbitra.ge//assets/frontend/images/arrow-downward.png)
Overview of AI, its history, and its applications
Key concepts and terminology
Machine Learning Fundamentals ![](https://skillarbitra.ge//assets/frontend/images/arrow-downward.png)
Supervised, unsupervised, and reinforcement learning
Common algorithms: linear regression, decision trees, clustering, etc.
Deep Learning Techniques ![](https://skillarbitra.ge//assets/frontend/images/arrow-downward.png)
Neural networks, convolutional neural networks (CNNs), recurrent neural networks (RNNs)
Training and optimizing deep learning models
Large Language Models (LLMs) ![](https://skillarbitra.ge//assets/frontend/images/arrow-downward.png)
Architecture and functioning of LLMs (e.g., GPT-4)
Training and fine-tuning LLMs for specific tasks
Prompt Engineering ![](https://skillarbitra.ge//assets/frontend/images/arrow-downward.png)
Techniques for designing effective prompts
Optimizing AI responses for accuracy and relevance
Natural Language Processing (NLP) ![](https://skillarbitra.ge//assets/frontend/images/arrow-downward.png)
Text preprocessing, tokenization, and embedding techniques
Applications in sentiment analysis, text summarization, and translation
Automatic Data Analytics ![](https://skillarbitra.ge//assets/frontend/images/arrow-downward.png)
Data collection, cleaning, and preprocessing
Automated analytics workflows and pipelines
Predictive Modeling ![](https://skillarbitra.ge//assets/frontend/images/arrow-downward.png)
Building and validating predictive models
Techniques for improving model accuracy and performance
Data Visualization ![](https://skillarbitra.ge//assets/frontend/images/arrow-downward.png)
Creating insightful visualizations using tools like Tableau and Power BI
Best practices for presenting data insights
Cloud-Based AI Services ![](https://skillarbitra.ge//assets/frontend/images/arrow-downward.png)
Overview of cloud platforms: AWS SageMaker, Google AI Platform, Azure ML
Deploying and managing AI models on the cloud
Big Data Technologies ![](https://skillarbitra.ge//assets/frontend/images/arrow-downward.png)
Introduction to big data frameworks like Hadoop and Spark
Processing and analyzing large datasets
Model Evaluation and Metrics ![](https://skillarbitra.ge//assets/frontend/images/arrow-downward.png)
Evaluating model performance using metrics like precision, recall, F1-score
Techniques for model validation and cross-validation
Ethics in AI ![](https://skillarbitra.ge//assets/frontend/images/arrow-downward.png)
Ethical considerations and challenges in AI development and deployment
Bias, fairness, and transparency in AI systems
AI in Industry Applications ![](https://skillarbitra.ge//assets/frontend/images/arrow-downward.png)
Case studies of AI applications in healthcare, finance, marketing, etc.
Exploring domain-specific AI solutions
Capstone Projects ![](https://skillarbitra.ge//assets/frontend/images/arrow-downward.png)
Hands-on projects that integrate course components
Real-world scenarios and business challenges
Course Plan
Standard
₹ 1499
incl. of all charges
1 online live class/ week (24 weeks)
2 practical assignments per week (24 weeks)
Get digital access to entire study material
Access on LMS, Android & iOS app
Instructor feedback on assignments
Doubt clearing on Discord, LMS & classes
Instructor led course with online live classes (recordings available)
Online exams (give exams as per your convenience on given time slots)
Certificate (by courier)
Training for writing and publishing articles
Networking with other students & alumni
Access to updated content online for 3 years
Doubt clearing within 24 hours