AI training institute ahmedabad

Data Science and Data Analysis Course Syllabus

Python Fundamentals
  • Basic Syntax and Data Types
  • Control Flow.
  • Functions
  • Object-Oriented Programming (OOP)
Data Handling with Python Libraries
  • NumPy : Working with arrays, performing numerical computations, and array manipulation.
  • Pandas : DataFrames and Series, reading/writing data from various file formats (CSV, Excel)
  • Data aggregation, grouping, cleaning, and merging.
  • Data Cleaning & Preprocessing : Handling missing data, removing duplicates
  • Feature scaling and normalization, and managing categorical data (label encoding, one-hot encoding).
Statistical Analysis and Probability
  • Descriptive Statistics: Measures of central tendency (mean, median, mode) and dispersion (variance, standard deviation).
  • Probability Theory: Basic concepts, conditional probability, and common probability distributions.
  • Inferential Statistics: Hypothesis testing, confidence intervals, and statistical significance.
Data Visualization
  • Matplotlib: Creating static, interactive, and animated visualizations such as line plots, scatter plots, and histograms.
  • Seaborn: Building statistical plots and improving the aesthetics of visualizations.
  • Plotly: Creating interactive and dynamic plots for web-based applications.
Tools and Environment
  • Jupyter Notebooks/Spyder: Setting up and using IDEs for interactive data analysis.
  • Working with Data: Understanding the data science lifecycle and applying Python tools at each stage.
  • Exploratory Data Analysis (EDA): Use Python to explore datasets, identify patterns, and check assumptions.
  • SciPy: Learn to use this library for advanced scientific computing, which includes statistical functions.
Projects and applications
  • Real-world projects :
  • Work on end-to-end projects that require you to apply the full data analysis workflow, from data collection to modeling and visualization.
  • Guided practice :
  • Apply learned skills to real datasets, such as analyzing stock market data or building a predictive model for a realistic business problem.

Duration : 5 Months

Eligibility : Knowledge of Core Python

Available Batches : Regular Batch -> Monday-Saturday
WeekEnd Batch -> Saturday and Sunday
Fast-Track Batch ->4 to 5 hrs daily
Present & Future Scope
  • Got placements in Mid and Large size co.s
  • Advantage of Open source - more acceptance
  • Mobile is future Technology - Helpful to build career
  • For long term it is good technology
  • Go for other technologies also for taking added advantage
  • Android applications are more developed comparing to iPhone
  • We are famous as Android training institute in ahmedabad.
Course Content :

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