Course Description
What you’ll learn?
- Understand the meaning, purpose, scope, stages, applications, and effects of Artificial Intelligence
- Master the key concepts of Python Programming, including all the core and advanced topics and how to apply statistics with the data
- Get an expertise in writing your own scripts in idiomatic approach by performing hands-on exploratory data analysis using Jupyter notebook
- Gain an in-depth understanding of different phases in the Data Science process like feature engineering, data exploration, data visualization, feature selection, model building, model evaluation
Who This Course is for
- Beginners in AI & ML space looking to kickstart their careers.
- Graduates looking to build a career in Artificial Intelligence and Machine Learning.
- Anyone with basic programming skills looking to boost their career in Machine Learning or Artificial Intelligence
- Experienced professionals who would like to harness Artificial Intelligence in their fields to get more insight
How will your doubts get solved?
You can post your doubts on the Q&A forum which will be answered by the teachers within 24 hours.
Course Content
- Module 1: Review of Python
- Topic 1.1: Input/Output Statements 10min
- Topic 1.2: Variables, Data types, Operators
- Topic 1.3: Control Statements
- Topic 1.4: Functions
- Topic 1.5: Data Structures: Strings, List,Tuple,Set,Dictionary
- Topic 1.6: Functional Programming and Idiomatic approach
- Topic 1.7: File Handling & Database Connectivity
- Topic 1.8: Modules, Packages and Core Libraries
- Module 2: Python Packages for Data Science Applications
- Module 3: Data Preprocessing
- Module 4: Exploratory Data Analysis
- Module 5: Introduction to Machine Learning
- Topic 5.1: Simple Linear Regression
- Topic 5.2: Multiple Linear Regression
- Topic 5.3: Logistic Regression
- Topic 5.4: K Nearest Neighbors
- Topic 5.5: Naive Bayes
- Topic 5.6: Decision Tree
- Topic 5.7: Ensembling Algorithms
- Topic 5.8: Cluster Analysis
- Topic 5.9: Dimensionality Reduction: PCA
- Topic 5.10: Hyperparameter Optimization
- Topic 5.11: Handling Imbalanced Data
- Module 6: Performance Evaluation of the models
- Module 7: Introduction to Neural Networks
Score Breakdown
4.2 / 5.0
Score Breakdown
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Average Rating For
- Content5.0
- Knowledge5.0
- Assignment5.0
- Classroom4.0
- Instructor5.0
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Good training and needed more expanded training sessions
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I have learn't a lot of things from this program and i'am happy for it. Instructors have given a clear picture on my project.
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It was a wonderful experience to do my internship at Dhyanahitha School of Professional Studies.
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This internship helped us very much, And our mentors are very good,that they clarified and explained every doubt clearly.Though we missed any of the class due to any reason,recorded videos helped a lot.finally this internship taught us how to learn the things and complete the project in given time.
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The Intership was very nice... thought out the course I could learn many new concepts...
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All the faculty of the internship were very supportive and helped us all time
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Very good explanation. Clear explanation of doubts.
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Explanation was good.Recorded session videos are quite helpful.Time period for internship is too long. During presentation of project every single time something need to be added.
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Was helpful to learn how to work on projects and use resources
You are not applied for the course..!
How will your doubts get solved?
You can post your doubts on the Q&A forum which will be answered by the teachers within 24 hours. You can post your doubts on the Q&A forum which will be answered by the teachers within 24 hours.
- Price To be Anounced
- Start Date To be Notified
- End Date To be Notified
- Course Type: To be Notified
- Total Slots: To be Notified
- Available Slots: 00
- Duration : To be Announced
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For more details contact: +91 9908762237
