Module 1: Introduction to Data Science (Duration-1hr)

  • What is Data Science?
  • What is Machine Learning?
  • What is Deep Learning?
  • What is AI?
  • Data Analytics & it’s types
  • Module 2: Introduction to Python (Duration-1hr)

    • What is Python?
    • Why Python?
    • Installing Python
    • Python IDEs
    • Jupyter Notebook Overview
    • Module 3: Python Basics (Duration-5hrs)

      • Python Basic Data types
      • Lists
      • Slicing
      • IF statements
      • Loops
      • Dictionaries
      • Tuples
      • Functions
      • Array
      • Selection by position & Labels
      • Module 4: Python Packages (Duration-2hrs)

        • Pandas
        • Numpy
        • Sci-kit Learn
        • Mat-plot library
        • Module 5: Importing data (Duration-1hr)

          • Reading CSV files
          • Saving in Python data
          • Loading Python data objects
          • Writing data to csv file
          • Module 6: Manipulating Data (Duration-1hr)

            • Selecting rows/observations
            • Rounding Number
            • Selecting columns/fields
            • Merging data
            • Data aggregation
            • Data munging techniques
            • Module 7: Statistics Basics (Duration-11hrs)

                Central Tendency

              • Mean
              • Median
              • Mode
              • Skewness
              • Normal Distribution
              • Probability Basics

              • What does mean by probability?
              • Types of Probability
              • ODDS Ratio?
              • Standard Deviation

              • Data deviation & distribution
              • Variance
              • Bias variance Trade off

              • Underfitting
              • Overfitting
              • Distance metrics

              • Euclidean Distance
              • Manhattan Distance
              • Outlier analysis

              • What is an Outlier?
              • Inter Quartile Range
              • Box & whisker plot
              • Upper Whisker
              • Lower Whisker
              • catter plot
              • Cook’s Distance
              • Missing Value treatments

              • What is a NA?
              • Central Imputation
              • KNN imputation
              • Dummification
              • Correlation

              • Pearson correlation
              • Positive & Negative correlation
              • Error Metrics Duration-3hr

              • Classification
              • Confusion Matrix
              • Precision
              • Recall
              • Specificity
              • F1 Score
              • Regression

              • MSE
              • RMSE
              • MAPE
              • Module 8: Machine Learning

                  Module 9: Supervised Learning (Duration-6hrs)

                    Linear Regression

                  • Linear Equation
                  • Slope
                  • Intercept
                  • R square value
                  • Logistic regression

                  • ODDS ratio
                  • Probability of success
                  • Probability of failure
                  • ROC curve
                  • Bias Variance Tradeoff
                  • Module 10: Unsupervised Learning (Duration-4hrs)

                    • K-Means
                    • K-Means ++
                    • Hierarchical Clustering
                    • Module 11: Other Machine Learning algorithms (Duration-10hrs)

                      • K – Nearest Neighbour
                      • Naïve Bayes Classifier
                      • Decision Tree – CART
                      • Decision Tree – C50
                      • Random Forest

                      Thanks for the best ever Training. I did my Android Course here. Trainer is very good in knowledge. They provides the best ever Support to me.

                      Kaviya