Best institute for DATA SCIENCE training IN  HYDERABAD

Data Science Training in Hyderabad

 

  1. Introduction to Data Science
  • Why it is important and who are eligible
  1. Use Cases/Business Application (Retail, CPG, Banking, Telecom etc.)
  • Different scenario where DS can be applied to solve business problems
  1. Basics of Statistics –
  • Descriptive Statistics for
  • Mean, Median, Mode, Quartile, Percentile, Inter-Quartile Range
  • Standard Deviation, Variance
  • Descriptive Statistics for two variables
  • Z-Score
  • Co-variance, Co-relation
  • Chi-squared Analysis
  • Hypothesis Testing
  1. Probability concepts –
  • Basic Probability, Conditional Probability
  • Properties of Random Variables
  • Expectations, Variance
  • Entropy and cross-entropy
  • Estimating probability of Random variable
  • Understanding standard random processes
  1. Data Distributions
  • Normal Distribution
  • Binomial Distribution
  • Multinomial Distribution
  • Bernoulli Distribution
  • Probability, Prior probability, Posterior probability
  • Naive Bayes Algorithm
  1. Basic Mathematics for Data Science
  • Limits,
  • Derivatives, Partial Derivatives
  • Gradients, Significance of Gradients
  1. Mastering Python/R Language
  • How to install python (Anaconda), sciKit Learn
  • How to work with Jupyter Notebook and Spyder IDE
  • Strings, Lists, Tuples, and Sets
  • Dictionaries, Control Flows, Functions
  • Formal/Positional/Keyword arguments
  • Predefined functions (range, len, enumerates etc…)
  • Data Frames
  • Packages required for data Science in R/Python
  1. Introduction to NumPy
  • One-dimensional Array, Two-dimensional Array
  • Pre-defined functions (arrange, reshape, zeros, ones, empty)
  • Basic Matrix operations
  • Scalar addition, subtraction, multiplication, division
  • Matrix addition, subtraction, multiplication, division and transpose
  • Slicing, Indexing, Looping
  • Shape Manipulation, Stacking
  1. Introduction to Pandas
  • Series, DataFrame, GroupBy
  • Crosstab, apply and map
  1. Data Preparation Techniques
  • Applications of PCA: Dimensionality Reduction
  • Feature Engineering (FE)
  • Combine Features
  • Split Features
  1. Data Visualization
  • Bar Chart
  • Histogram
  • Box whisker plot
  • Line plot
  • Scatter Plot and Heat Maps
  1. Machine Learning Algorithm – Data Preparation and Execution
  • Linear Regression
  • Logistic Regression
    • Optimization (Gradient Descent etc.)
  • Decision Tree
  • Random Forest
  • Boosting and AdaBoost
  • Clustering Algorithms (KNN and K-Means)
  • Support Vector Machines
  • Nave Bayes Algorithm
  • Neural Networks
  • Text Mining (NLTK)
  • Introduction to Deep learning

Note: All these Algorithms will be explained using one case study and executed in python.  

Data Science Training in Hyderabad

Kosmik Provides Data Science training in Hyderabad. We are providing lab facilities with complete real-time training. Training is based on complete advance concepts. So that you can get easily “hands-on experience”. We will give 100% job assistance.