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GOOGLE AI-ML VIRTUAL INTERNSHI FROM AICTE EDU SKILL
- 1. AN INTERNSHIP FINALREPORT ON GOOGLE AI-ML VIRTUAL INTERNSHIP SUBMITTED TO SRINIVASA INSTITUTE OF ENGINEERING AND TECHNOLOGY BACHELOR OF TECHNOLOGY CIVIL ENGINEERING SUBMITTED BY D.HARITHA SRI NANDINI Roll No. 216N1A0111 DEPARTMENT OF CIVIL ENGINEERING, SRINIVASA INSTITUTE OF ENGINEERING AND TECHNOLOGY, NH-216, CHEYYERU-533216
- 2. SRINIVASA INSTITUTE OFENGINEERING AND TECHNOLOGY (UGC – Autonomous Institution) (Approved by AICTE, Permanently affiliated to JNTUK, Kakinada, ISO 9001: 2015 certified Institution) (Accredited by NAAC with 'A' Grade; Recognised by UGC under sections 2( f) & 12(B)) NH-216, Amalapuram-Kakinada Highway, Cheyyeru (V), Amalapuram-533216. DEPARTMENT OF CIVIL ENGINEERING CERTIFICATE This is to certify that the Summer Internship Report on “GOOGLE AI-ML VIRTUAL INTERNSHIP” carried at GOOGLE ACADEMY is submitted by DAIVALA HARITHA SRI NANDINI(216N1A0111) is a student of IV B Tech Civil Engineering at Srinivasa Institute of Engineering and Technology, Amalapuram. she completed the internship during the summer vacation between 3rd year and 4th year from 2023 to 2024. Mentor Principal Head of the Department
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- 4. Google AIML Virtual Internship Welcometo the Google AI/ML Virtual Internship program. This program is designed to provide a comprehensive and immersive experience for aspiring data scientists and machine learning engineers. As AI has boomed in recent years, it’s become commonplace in both business and everyday life. People use AI every day to make their lives easier interacting with AI-powered virtual assistants or programs. Companies use AI to streamline their production processes, project gains and losses, and predict when maintenance will have to occur.
- 5. Intro to GoogleAIML AI & ML Fundamentals Learn the core principles of artificial intelligence and machine learning, covering algorithms, techniques, and applications. Google Could Platform Gain hands-on experience with Google Cloud Platform's AI and ML tools, including BigQuery, TensorFlow, and Cloud AI Platform. Real World Use Cases Explore how AI and ML are transforming various industries, from healthcare to finance, and learn about real-world applications.
- 6. Key Internship Objectives Develop Technical Skills Enhance your proficiency in Python, machine learning algorithms, and data analysis techniques. Build Practical Projects Work on challenging and impactful projects that showcase your skills a And knowledge Gain Industry Exposure Experience the real-world applications of AIML and learn about Google's approach to innovation. Network with experts Connect with Google mentors, industry professionals, and fellow interns to gain valuable insights and build your network.
- 7. Project Tracks and Specializations •Computer Vision Develop algorithms for image recognition, object detection, and image segmentation. • Natural Language Processing Explore text analysis, machine translation, and sentiment analysis using AI techniques. • Data Science Apply data mining, statistical modeling, and predictive analytics to solve real-world business problems.
- 8. Technical Curriculum and Training OnlineCourses Access self-paced courses on Google Cloud AI, TensorFlow, and other relevant topics. Interactive Workshops Participate in hands-on workshops led by Google experts, covering specific AIML techniques. Technical Mentorship Receive personalized guidance and support from Google engineers throughout the internship.
- 9. Hands-on Learning Experiences ProjectDevelopment Work on real-world projects aligned with your specialization, applying your skills and knowledge. Data Analysis and Visualization Use Google Cloud tools to analyze large datasets, visualize trends, and extract valuable insights. Model Deployment Learn to deploy and scale your AIML models using Google Cloud infrastructure.
- 10. Mentorship and Networking Opportunities MentorshipConnect with Google engineers for guidance, feedback, and career advice. Peer Networking Collaborate with fellow interns, share knowledge, and build connections within the AIML community. Industry Events Attend virtual events to learn from industry leaders and explore emerging trends in AIML.
- 11. Advantages of aiml Improvedefficiency AIML automates tasks, freeing up human resources for more strategic activities. Enhanced Accuracy AIML algorithms can process data with minimal errors, reducing the risk of human bias. Increased Innovation AIML enables new possibilities for product development, business models, and problem-solving. Cost Reduction AIML can optimize processes and reduce operational costs, leading to greater profitability.
- 12. • Reducing humanerror • First and foremost, AI excels at reducing many of the errors that an average human being can make – a critical factor in data-driven decision-making • Minimizing costsPerhaps • even more importantly than reducing errors, AI can greatly decrease operating costs. By automating tasks that would otherwise require extensive human labor, businesses can significantly reduce their expenditures. This is especially prominent in industries where there are many routine tasks that can be effectively handled by AI systems, such as finance and e-commerce, freeing up human resources for more strategic decision-making roles.
- 13. Applications of AIML Healthcare AIMLis used for disease diagnosis, drug discovery, and personalized medicine. Finance AIML is used for fraud detection, risk assessment, and personalized investment advice. Retail AIML is used for product recommendations, customer segmentation, and inventory management.
- 14. Conclusion AI isat the centre of a new enterprise to build computational models of intelligence Now the great challenge of AI is to find ways of representing the commonsense knowledge and experience that enable people to carry out everyday activities. The future of Technology&society. Rivals Human Intelligence. Rises difficult Ethical Issues.