What you'll learn in Python for Data Analytics
Python built for analysts: Pandas, NumPy and charts, then statistics, SQL integration and automating Excel and email reports, ending with real analytics projects and interview prep.
01Python Fundamentals4 topics
- Why Python for analytics; Python vs Excel vs SQL
- Installing Python, Anaconda & Jupyter
- Variables, data types, type casting, input / output, f-strings
- Arithmetic, relational, logical & assignment operators
02Control Flow & Data Structures4 topics
- if / elif / else and nested conditions
- for & while loops; break, continue, pass
- Lists, tuples, sets & dictionaries
- List & dictionary comprehensions
03Functions & Modules3 topics
- User-defined functions, arguments & returns
- Lambda functions
- Built-in modules & external libraries
04NumPy3 topics
- Arrays, creation & reshaping
- Indexing & slicing
- Mathematical & aggregation functions
05Pandas for Data Analysis4 topics
- Series & DataFrames; importing CSV & Excel
- Missing values, duplicates, type conversion, string operations
- Filtering, sorting & Group By
- Merge, join, concatenate; pivot tables & crosstab
06Data Visualisation3 topics
- Matplotlib & Seaborn
- Line, bar, histogram, box plot, heatmap
- Scatter & pie plots; saving charts
07Statistics & EDA5 topics
- Descriptive statistics, skewness, variance, standard deviation
- Covariance & correlation
- Probability, normal distribution, Central Limit Theorem
- Confidence intervals & hypothesis testing
- Univariate, segmented & bivariate analysis; derived columns
08Date, Time & Text2 topics
- datetime module & time-series basics
- String manipulation & regular expressions
09Python with SQL3 topics
- Connecting Python to databases
- Reading & writing data
- Running SQL queries from Python
10Automation & Reporting3 topics
- Reading & writing Excel with Pandas; openpyxl
- Automating MIS reports
- File, folder & email automation
11Projects & Interview Prep4 topics
- Sales, HR & finance analytics projects
- Dashboard-ready datasets for Power BI / Tableau
- Python interview questions for data analysts
- Resume & project discussion
⬇ Download Python syllabus PDFFull syllabus page
Programs that include Python for Data Analytics
| Program | Duration | Fees |
|---|---|---|
| Advance MIS & Analytics | 4–6 months | ₹20,000 |
| Professional MIS & Analytics + Job Placement | 6–8 months | ₹30,000 |
| Professional Data Science & AI (GenAI, ML & Agentic AI) | 10–12 months | ₹75,000 + GST |
Need only Python for Data Analytics for your current job? Ask the counsellor about module-wise batches.
Why learn Python for Data Analytics with us?
- Taught on real company MIS reports, not textbook examples
- Topic-wise practice tests on our student portal, with weak-topic tracking
- Weekday, weekend and live online batches
- Classroom branches in Dwarka, Uttam Nagar and Janakpuri
Frequently asked questions
Is the course offered online or offline?
Both. You can join classroom batches at our Dwarka, Uttam Nagar or Janakpuri branch, or attend live online classes. Corporate training is also available.
What are the course fees?
Basic MIS & Analytics is ₹10,000 (3–4 months), Advance MIS & Analytics is ₹20,000 (4–6 months) and Professional MIS & Analytics + Job Placement is ₹30,000 (6–8 months). Easy instalments are available.
Do I get a certificate?
Yes. You receive a certificate after completing at least 90% of the content, assignments and attendance, and submitting one medium-level project.
Do you provide placement support?
Yes. We provide placement assistance including aptitude training, resume building, mock interviews, LinkedIn profile building and interview referrals.
Are there any prerequisites?
No. 12th pass with basic English is enough. The course starts from fundamentals, so students from any background can join.
Available at
Python for Data Analytics course in Dwarka · Python for Data Analytics course in Uttam Nagar · Python for Data Analytics course in Janakpuri · Live online