News and Announcement

Certificate in Data Science and AI Application Development

Wednesday, October 16, 2019

Center for Enterprise Technology Advancement(CETA), HSM is going to arrange 2 Months Training Workshop on "Certificate in Data Science and Artificial Intelligence Application Development"

The course will include the following sessions:

Basic Concepts and Python (1st Session)

  1. Introduction
  2. Why you should learn data science?
  3. What you will learn in this course?
  4. Intro to Anaconda, Jupyter notebook and Python
  5. Hands-on basic programming with Python: Variables, Conditions, Loops, Arrays, Lists, Dictionary
  6. Intro to Python libraries: Numpy, Pandas, Keras, Scikit-Learn, Matplotlib, Plotly, nltk
  7. Intro to HackerRank, mettl and leetcode for programming 
  8. Intro to Kaggle, github and google colaboratory 
  9. Learning Material 
  10. Real life project/assignment

Statistics (2nd Session)

  1. Why Statistics is mandatory for Data Science?
  2. IBM SPSS Statistics
  3. Data Types and Variables
  4. Data Description
  5. Regression Analysis, Model and Types
  6. Linear Regression Interpretations and Assumptions
  7. Logistic Regression, Types, Interpretations and Assumptions
  8. Factor Analysis
  9. Assignment 

Linear Algebra and Math (3rd Session)

  1. How Linear Algebra is applied in Data Science?
  2. Scalars, Vectors and Matrices
  3. Multiplying Matrices and Vectors
  4. Identity and Inverse Matrices
  5. Special Kinds of Matrices and Vectors like Diagonal, Symmetric, Orthogonal
  6. Multivariate Analysis
  7. Dimensionality Reduction, Factor Analysis and PCA
  8. Assignment 

Data Mining (4th Session)

  1. CRISP-DM model
  2. Introduction of few tools like Tableau, PowerBI, Orange, Weka, Knime
  3. Classification, Association, Outlier detection, Clustering, Regression
  4. Data Exploration
    1. Categorical and quantitative data
    2. Histograms
    3. Scatterplots
  5. Data Wrangling, Data Visualization, Bootstrapping
  6. K-mean clustering on telco data and churn prediction 
  7. Data Quality report 8. Preparation of effective presentation for a successful data scientist 9. Real life project/assignment 

Natural Language Processing (5th Session)

  1. How does Natural Language Processing Works?
  2. Linguistic terminology
  3. Syntax techniques
    1. Morphological segmentation
    2. Word segmentation
    3. Part-of-speech tagging
    4. Parsing
    5. Sentence breaking
    6. Stemming
  4. Semantics techniques
    1. Named entity recognition (NER)
    2. Word sense disambiguation
  5. Intro to applications of NLP 
    1. Machine Translation, Text Categorization, Spam Filtering, Information Extraction, Summarization, Dialogue System
  6. Real life project/assignment

Machine Learning (6th and 7th Session)

  1. Intro to Machine Learning
  2. Data Modeling
  3. Training and testing data
  4. Supervised and unsupervised learning
  5. Feature Selection, Feature Engineering and Data Pipelines
  6. Important regression algorithms
    1. Simple Linear Regression
    2. Multiple Linear Regression
    3. Decision Tree
    4. Random Forest
  7. Important classification algorithms
    1. Logistic Regression.
    2. K-Nearest Neighbours (K-NN)
    3. Support Vector Machine (SVM)
    4. Naive Bayes
    5. Decision Tree
    6. Random Forest
  8. Important regression algorithms
    1. K-Means Clustering
    2. Hierarchical Clustering
  9. Assessing your model
  10. Drawing insights from your model
  11. Cross Validation
  12. Real life project/assignment

Deep Learning (8th Session)

  1. Neural Network
  2. Tensor Flow/Keras
  3. IBM Watson Studio
  4. Intro to IBM cloud applications for Visual Recognition, Tone Analyzer and Personality Insights
  5. Introduction to IBM free badges and certificates

Trainer: Mr. Fakhar Abbas (Senior Data Scientist at IBM)

Starting Date: October 15, 2019 (Evening Classes)

Fee: Rs. 20,000/-

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