When is the Right Time to Explore Data Science and AI: From Plus 2 to College students and Beyond

If you are in your 12 grade, or if you are an undergraduate student in college keen to know when and how to start your career in Data Science and AI/ML, this free Masterclass is perfect for you. This Masterclass covers the essential steps you need to take to discover Data Science and Artificial Intelligence early in your career.

You will know about the core principles, applications, techniques and tools ruling the Data Science and AI ecosystem. You will get an overview of Machine Learning, its foundations, types of ML algorithms and use cases of ML.

You will get insights into industry trends and job roles in DS and AI, and valuable advice on how to kickstart your career path in the Data Science and AI landscape. You must seize this opportunity to interact with our speaker and get your questions about your career answered. Remember, the earlier you start with Data Science and AI, the better prepared you are to build your career.

Join this free Masterclass, and give yourself a competitive advantage today.

Key Takeaways :-

• How to Kickstart your DS and AI Career Early in Grade 12, or during College years
• Learn about the fundamentals of Data Science and AI and how they are applied in different industries.
• Gain insights into the latest trends and technologies shaping the field of Data Science and AI.
• Explore diverse career paths in data science, such as data analyst, ML engineer, and AI researcher.
• Understand how to build a successful career in Data Science and AI and what skills are required to succeed in the field.
• Emphasize continuous learning and stay updated with the latest advancements.
• Network with other like-minded individuals and connect with experienced professionals in the industry.
• An opportunity to ask career related questions and interact with our expert presenter on the topic.

A Certificate of Participation will be provided by CloudxLab to all the attendees who fill in the Participation form.