ARTIFICIAL INTELLIGENCE TRAINING

Module 4 -Python programming

• Introduction to python
• Operators
• Data Types
• Control Statements
• Functions
• Data Structures – Lists, Sets, Tuples, Strings, Dictionaries,
• OOPS Concept
  

   

  Module 5 -Libraries

  • Numpy
  • Pandas
  • Scipy
  • Scikit-Learn • Keras

  • Matplotlib • Seaborn
  • Cufflinks • NLTK

  Note: Installations and work end to end. As per requirements going to work with different libraries.

Module 6 – Data Exploration

• Collecting data from different sources
• Analyzing data
• Data preprocessing
• Data munging
• Data mining
• Data manipulation
• Data visualization
• Feature Selection
• Feature Scaling
• Dimensionality reduction
  

  Module 7 -Statistics

• Basics of Statistics
• Descriptive Statistics
• Inferential Statistics
• Qualitative vs. Quantitative Analysis
• Hypothesis Testing
• Data Distribution
  

  Module 8 – Other Mathematics Concepts

• Probability
• Calculus
• Linear algebra
  

  Module 9 -Machine Learning

• Introducing Machine Learning models
• Supervised learning
• Regression and Classification models
• Unsupervised learning
• Clustering and Aggregation models
• Semi supervised learning
• Over fitting and under fitting(Linear, Logistic, Navi Bayes, K-Nearest Neighbors, Support Vector Machine, Decision Trees, Random Forest …..)Note: Deals with Mathematics and Programming part
  

  Module 10 -Deep Learning and other algorithms

• Introduction to Deep learning
• OpenCV
• Artificial Neural Networks
• Convolutional Neural Networks
• Recurrent Neural Networks
• Tensor flow
• Over fitting and under fitting

Module 11 -Natural Language Processing

• Introduction to NLP
• Text Preprocessing
• Lemmatization
• Stemming
• Text to features
• Important Tasks in NLP
• Important Libraries for NLP
  

  Module 12 – Computer Vision

  WORKING ON DATA SCIENCE PROJECTS

• Examine your problem
• Prepare your data (raw data, feature extraction, feature engineering, etc.)
• Spot-check a set of algorithms
• Examine your results
• Double-down on the algorithms that worked bestNote: Deals ‘n’ number of real time projectsWORK ENVIRONMENT

• Status meetings
• Meetings with stockholders
• Participating in gathering requirements
• Working on client projects
• Coordinating team

System Requirements

• Ram 4GB Min
• Hard Disk 250GB
• Processor i3 Min