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MIT ADT University BCA in Artificial Learning & Machine Learning (AL-ML)

BCA in Artificial Learning & Machine Learning (AL-ML) at MIT ADT University - Course, Fees, Admission, Seats, Syllabus

location Pune ( Maharashtra )
location Estd In: 2015
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BCA in Artificial Learning & Machine Learning (AL-ML) at MIT ADT University - Course, Fees, Admission, Seats, Syllabus
location
Pune ( Maharashtra )
location
Estd In: 2015
Last Updated on February 20, 2024 5:00 PM
MIT ADT University, an institution known for its innovative approach to education offers an advanced Bachelor of Computer Applications (BCA) program in Artificial Learning & Machine Learning (AL ML). This program is carefully designed to provide students with the knowledge and skills to excel in the ever evolving fields of artificial intelligence and machine learning. The curriculum covers subjects like Neural Networks, Deep Learning, Natural Language Processing and Robotics to ensure a comprehensive grasp of the subject matter. The BCA in AL ML program has limited seats emphasizing a focused and interactive learning environment. However the exact number of seats and fee structure may be subject to updates which can be confirmed directly through the universitys admissions office. Admission to this program is competitive requiring candidates to successfully pass an entrance exam recognized by the university that evaluates their aptitude in relevant areas. What sets this program apart is not its academic rigor but also its emphasis on practical and hands on experience that prepares students, for successful careers in the dynamic field of artificial intelligence and machine learning.
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MIT ADT University BCA in Artificial Learning & Machine Learning (AL-ML) Highlights 2024

Course DurationCourse LevelCourse Tuition FeesMode of StudyInstitute Type
3 YearsUndergraduateVaries by YearFull-timePrivate

MIT ADT University BCA in Artificial Learning & Machine Learning (AL-ML) Syllabus 2024

As of my last update in April 2023, I don't have access to real-time databases or the specific syllabus details for courses at MIT ADT University or any other institutions. Course syllabi can vary significantly from year to year, and it's best to consult the university's official website or contact the university directly for the most current and detailed syllabus. However, I can provide you with a general outline of what a BCA in Artificial Learning & Machine Learning (AL-ML) program might cover. Please note, this is a generic template and not specific to MIT ADT University:
YearSemesterSubjects
11Introduction to Programming, Mathematics for Computer Science, Introduction to Artificial Intelligence
12Data Structures and Algorithms, Database Management Systems, Principles of Machine Learning
21Object-Oriented Programming, Linear Algebra for Machine Learning, Deep Learning Fundamentals
22Software Engineering, Statistics for Machine Learning, Neural Networks and Applications
31Natural Language Processing, Computer Vision, Elective 1 (e.g., Robotics, IoT, etc.)
32Big Data Analytics, Reinforcement Learning, Project Work / Internship
This table is a simplified representation and should be used as a basic guideline. For accurate and detailed information, please refer to the official curriculum provided by MIT ADT University.

MIT ADT University BCA in Artificial Learning & Machine Learning (AL-ML) Important Topics 2024

As of my last update in April 2023, specific syllabus details for the BCA in Artificial Learning & Machine Learning (AL-ML) specialization at MIT ADT University may vary and should be verified directly with the institution for the most current information. However, I can provide you with a general overview of important topics that are typically covered in such programs. Please note that this is a generic list and the actual syllabus may include more or different topics. For a detailed and accurate syllabus, you should consult the official MIT ADT University resources. Here's a simplified single-line HTML format representation of what the syllabus might include, based on common topics covered in similar programs:
Core TopicsRelated Technologies/Tools
Introduction to ProgrammingPython, Java
Data Structures and AlgorithmsPython, C++
Mathematics for Machine LearningLinear Algebra, Calculus, Statistics
Principles of Machine LearningScikit-learn, TensorFlow
Deep LearningTensorFlow, Keras
Natural Language ProcessingNLTK, SpaCy
Computer VisionOpenCV, TensorFlow
Reinforcement LearningPyTorch, TensorFlow
Big Data TechnologiesHadoop, Spark
Cloud Computing for AIAWS, Azure, GCP
This table includes a mix of theoretical foundations, practical programming skills, and exposure to various tools and libraries commonly used in the field of Artificial Intelligence and Machine Learning. Remember, the actual syllabus may include additional topics or specific courses on recent advancements in AI and ML, so it's essential to check the latest curriculum provided by MIT ADT University.

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