Brief Summary
This YouTube video introduces a new data science and AI course in Tamil, designed to simplify complex concepts for the Tamil-speaking community. The instructor, AI Coach John, addresses common concerns about coding difficulty and the overwhelming nature of data science. He outlines a learning strategy involving watching, doing, and community interaction, with an option for a paid community. The course includes certification, and the video shares John's background, achievements, and motivations for teaching, aiming to inspire and guide aspiring data scientists.
- Course is designed to simplify complex concepts for the Tamil-speaking community.
- Learning strategy involves watching, doing, and community interaction.
- Includes certification.
Introduction: Data Science Scope and Addressing Concerns
The video addresses the future scope of data science, AI, machine learning, and related topics, acknowledging the widespread interest in entering these fields. It recognises the common concerns and fears surrounding coding and the complexity of data science. Many individuals struggle to find the right resources and mentors to guide them effectively. AI Coach John aims to simplify these concepts for the Tamil community by providing accessible education and guidance.
Course Structure and Learning Strategy
The "Data Science with Machine Learning" playlist will feature daily video releases. A three-step learning strategy is introduced: "I do, you see," "I do, you do" (parallel work), and "You do, I see." The third step is reserved for paid community members, but the playlist is designed to be beneficial even without payment. Viewers are encouraged to subscribe, share the playlist, and take notes while watching the videos. A certification will be available upon completion of the program, with instructions revealed in the final episode.
About AI Coach John: Background and Achievements
AI Coach John shares his background, including his experience as a data scientist and team leader in a company focused on self-driving cars. He co-authored a book and has been training individuals in the AI field, transitioning careers and helping them succeed in the industry. John discusses his work on video-based data annotation and prediction projects for self-driving cars, as well as his involvement in recommendation engine and chatbot projects.
Overcoming Challenges and Motivation for Teaching
John reveals that he was an average student with arrears during his college years, engaging in activities like MLM and selling SIM cards. He highlights the challenges of outdated educational materials and the difficulty in securing employment. His personal struggles motivated him to help others facing similar obstacles in entering the IT industry. He aims to provide proper guidance and facilitate their placement as data scientists.
Experience with Career Transitions and Success Stories
John clarifies that he trains both freshers and experienced professionals, citing a success story of an individual with nine years of experience in sales and banking who transitioned into data science. He has assisted individuals with significant career gaps, those transitioning from teaching or automotive engineering, and placed them in reputable companies. Salaries for freshers range from â‚ą40,000 to â‚ą80,000 per month, and career transitions typically see a 30% salary increase.
Balancing Coaching and Consulting
John explains that he balances coaching with consulting, driven by a passion to guide individuals who lack proper support and one-on-one mentorship. He aims to prevent them from struggling and provides coaching to address this gap. Additionally, he consults with companies on product development, leveraging a team to conduct ground research and stay updated with the latest advancements in AI.
One-on-One Coaching and Mentorship Structure
The one-on-one coaching involves live sessions and research into trending topics like generative AI. Recognising the challenges of consistent live participation, the program shifted to a guidance-based model. Each participant is supported by a team of three data scientists, including John, for five to nine months. This includes resume building, project opportunities, internship experience, soft skills training, and potential hiring within their projects. A 3-on-1 mentorship group is available for doubt clarification, along with tools like time trackers and job application trackers.
Course Duration, Certification, and Internship Focus
John addresses the common claim of completing data science courses in just one or two months, emphasising that mastering skills requires four to six months with proper guidance. While they provide course completion certificates, the focus is on internship certifications, which hold higher value in the industry. Participants gain experience through project work, and those who excel receive internship letters or work experience letters, potentially leading to internal or external job opportunities.
Course Fees, EMI Options, and Time Commitment
The course is a "4-in-1" program covering data analysis, data science, AI, and generative AI, offered at 50% less than the market price. EMI options are available. Many participants study while working, utilising the one-on-one mentorship model. Students can study at their own pace, updating mentors on their progress for individualised support.
Placement Assistance and Long-Term Support
Unlike programs that end after training, this course provides ongoing mentorship until participants secure a job. Mentors offer contact numbers and support throughout the journey. Successful students may have opportunities for interviews and hiring within the company. The training includes communication skills development in English, preparing students for client interactions. The company's coaching and consulting services create internal opportunities, and the program aims to equip students with the skills needed for market success.
Call to Action and Next Steps
The video concludes with a call to action, inviting interested viewers to enquire about the paid mentorship program via the provided link. Beginners are encouraged to continue with the free course to gain clarity. Viewers are asked to share their motivational takeaways in the comments. The next episode will cover the course agenda, followed by foundational theory sessions and hands-on Python sessions.
