Data Science – Al-Nafi


Data Science

This training session provides practical foundation level training that enables immediate and effective participation in data mining and other analytics projects. It includes an introduction to data science and the Data Analytics Lifecycle to address business challenges that leverage big data. Read More

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Course Description

It provides grounding in basic and advanced analytic methods. Labs offer opportunities to understand how these methods and tools may be applied to real world business challenges by a practicing data scientist.

Course Contents

  1. Introduction
    • What is Data Science?
    • What is Big Data?
    • Define Data Context
    • Data Science Lifecycle
  2. Learning Python
  3. Data Assortment & Cleansing
    • Intro
    • Data Extractions
    • Data Preprocessing
  4. Exploratory Analysis
    • Introduction to Exploratory Graphs
    • Principles of Analytic Graphics
    • Plotting Systems in R
  5. Inferential Statistics
    • Introduction of Statistical Inferences
    • Inferential Statistics & Techniques
    • Statistics for Model Building and Evaluation
  6. Machine Learning
    • Introduction to Machine Learning
    • What is Prediction?
    • Prediction Study Design
    • Supervised Learning
      • Classification
      • Regression
    • Unsupervised Learning
      • Clustering
      • Association Rule Mining
    • Advance Analytics
      • Forecasting Models - Time Series Analysis
      • Text Analytics
    • Model Evaluation Techniques
      • Type of Errors
      • Receiver Operating Characteristic (ROC) Curves
      • Cross Validation
  1. Reproducible Research
    • Introduction to Reproducible Research
    • Organizing the Analysis & Coding Standard
    • Evidence based Data Analysis
    • Data Visualization & Data Products

Course Delivery Mode

The training will be delivered online via our portal, which is designed to cater 50 Million Nafi members. The portal has all the key features like:

  • Watching and tracking videos in Urdu and English,
  • Progress monitoring,
  • Attempting quizzes,
  • Submitting assignments,
  • Asking questions from the teachers and mentors
  • Access to flashcards