A typical data science course in Pune syllabus covers a range of topics designed to build skills in data analysis, machine learning, and programming. Below are the key components:

1. Introduction to Data Science

• Overview of data science concepts and its applications.
• Understanding data science workflows and tools.

2. Programming Fundamentals

• Python or R programming basics.
• Libraries like NumPy, Pandas, and Matplotlib for data manipulation and visualization.

3. Statistics and Probability

• Descriptive and inferential statistics.
• Probability distributions, hypothesis testing, and statistical significance.

4. Data Wrangling and Preprocessing

• Handling missing data, data cleaning, and formatting.
• Data normalization and transformation techniques.

5. Data Visualization

• Creating charts, graphs, and dashboards using tools like Tableau, Power BI, or Seaborn.

6. Machine Learning

• Supervised and unsupervised learning.
• Algorithms like regression, decision trees, clustering, and neural networks.

7. Big Data and Data Engineering Basics

• Introduction to big data tools like Hadoop and Spark.
• Understanding data pipelines and ETL processes.

8. SQL and Databases

• Querying databases using SQL.
• Data retrieval and management.

9. Natural Language Processing (NLP) (Optional)

• Text preprocessing, sentiment analysis, and language models.

10. Deep Learning (Optional)

• Neural networks, TensorFlow, and PyTorch basics.