Data Science with Python

by Institute of IT Training Canada Claim Listing

Data Science with Python Real-time learning of data science with Python. Weekends only. Course highlights: Why data science, what is the market, and what are companies looking for? Real-time learning of data science with Python.

R1499

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Course Details

Data Science with Python Real-time learning of data science with Python. Weekends only. Course highlights: Why data science, what is the market, and what are companies looking for? Real-time learning of data science with Python.

 

Course Highlights:

  • Why data science? What is the market, and what are companies looking for? (1%)

  • Data science overview (2%)

  • Data Analytics overview (2%)

  • Python environment set up, installations of IDE (5%)

  • Python learning from basics to advanced (30%)

  • Session 2 (10%):
    • Introduction to Business Analytics
    • Business Analytics and Competitive Advantage
    • Business Data and Systems
    • Data Lifecycle (DLC) and Data Quality

  • Session 3 (10%): Descriptive Analytics, Part 1
    • Introduction to R and Working with Data in R
    • Exploratory Data Analytics
    • Measures of Central Tendency and Variation
    • Exercise on Data Quality

  • Session 4 (10%): Descriptive Analytics, Parts 2 and 3
    • Associative Data Analytics (Correlation and Association)
    • Strategic Data Acquisition for Analytics
    • Inferential Data Analytics (T-Test, A/B Testing, and ANOVA)

  • Session 5 (10%): Predictive Analytics and Machine Learning
    • Fundamentals of Predictive Analytics
    • Regression Models: Simple Linear Regression and Multiple Linear Regression
    • Fundamentals of ML (Machine Learning)
    • Supervised and Unsupervised ML Algorithms
    • Exercise on Multiple Linear Regression (MLR)

  • Session 6 (10%): Prescriptive Analytics and Data Products
    • Introduction to Prescriptive Analytics
    • Applying Prescriptive Analytics Techniques for Optimal Results
    • Data Products
    • Times-series data and Fast Fourier Transform (FFT) Analysis
    • Text Analytics in Enterprises
    • Good Analytics vs. Bad Analytics

  • Session 7 (10%): Data Visualization and Wrap-up
    • Dashboards and Reports
    • Overview of Data Visualization
    • Data Visualization principles of Edward Tufte
    • 6 building blocks of Data storytelling, including Gestalt Principles
    • Managing your careers in Data Analytics
    • Wrap-up

  • Object-Oriented Programming Concepts

  • Operating Systems and Networks

  • Types of software development models

  • Rapid Application Development for OOSD

  • Security for Developers

  • Web Application Development

  • Database Development

  • .NET Web Applications

  • Open-source Source applications

  • Object-Oriented Practicum

  • Threaded Project for OOSD

  • Software Project Concepts

 

  • Calgary Branch

    2770 3rd Ave NE, Calgary

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