Advanced Data Science using Python
AI and Data Science are intertwined fields, with AI encompassing a broader scope of intelligent system development and Data Science focusing specifically on extracting knowledge and insights from data. The collaboration between these fields is crucial for building advanced and effective AI systems.
AIML
Start Date: December 26 2023​
What you'll learn
- In this Program, you will gain proficiency in how to analyze a number of statistical procedures in SPSS.
- Learn how to write the results of statistical analyses using APA format
- You will learn how to interpret the output of a number of different statistical tests
Approach
- Lead by industry experts
- Hands-on
- Real time project implementation
- Industry certificate
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- Python
- Data science
- Machine learning
- Google Colab
- GPU
Course content
15 Conceptual Sessions followed by Project implementation
- Fundamentals of Python language – basic syntax, Data structures, operators, conditional statements, loops, function, class.
- Woking with libraries, python libraries, installation and usage for writing the AI ML Mode ex – Tensorflow , Keras, Matplot, Pandas etc.
- AI ML – Data Science, Machine learning and NLP based concepts exploring
- AI ML models – Classification and regression models
- Model architecture, parameters, implementation flow and working.
- Feed Forward Network, Convolutional Neural Network, Recurrent Neural Network …. Etc.
- Method of implementation for own AI and ML model
- Annotation methods and Tools, Data cleaning and Augmentation methods with python coding.
- Training and Testing the ML model in the Google colab, TensorFlow and GPU system for various ML models.
- Hands on with basic python programming
- Projects on function, class and data processing in python
- Python Libraries based projects – Numpy, Pandas, Opencv, Matplot, Tensorflow, and Keras.
- Regression based projects like – Linear regression, Binary tree implementation on real time use cases example price prediction for crops, homes etc.
- ML project implementation in TensorFlow, Anaconda, Spyder and Google Colab for MNIST handwritten datasets, fashion MNIST datasets and Kaggle datasets and own dataset.
- Hands-on
- Industry based use cases
- 15 days Concepts oriented sessions followed by next 15 days self work
- Online Mode- Monday to Friday (1 Hr)
- Offline at Bangalore
- Complete Python programming Knowledge
- Industry Oriented expose for implementing the ML Models
- Hands on with real time use cases
Knowledge of all Machine learning Models and its implementation methods as per industry perspective.
- Basic level of programming understanding L0
- Knowledge of system handling for the python installation, VS code or any other python interpreter. (Anaconda, Spyder, Jyupter Notebook)
Highlights:
- Introduction to statistics course (either currently taking or already have completed) is recommended but not absolutely necessary
- Access to IBM SPSS Statistical software (strongly recommended)
Featured Review
I have done my one-month internship on AI & ML domain in DLithe in MITE College. It was a great learning experience, as I can practically implement the concepts I learnt. Here they make sure that each student understands the concept.
I have done my one month internship on Python with AI & ML domain in DLithe. It was a great learning experience, as I can practically implement the concepts I learnt. Here they make sure that each student understands the concept. It was an online internship so daily we had online training session on coding for 15 days and in the remaining 15 days we had to work on our project and submit it. It was very helpful to learn.
The internship was very interactive. Concepts were explained with more examples. l was able to learn team building skills and use it, which helped in implementation of the project in group.
I had the pleasure of participating in the AI and ML Internship at DLithe and I am very pleased with my experience. The Industrial mentors were very knowledgeable and helpful and provided me with the necessary guidance and materials to develop my skills. The topics covered in the program were comprehensive and relevant to the current trends in the field of AI and ML
