★★★★★ 4.8 / 5  ·  900+ reviews

Data Science
with Machine Learning

Build intelligent systems — from raw data to deployed ML models. The most comprehensive data science program, designed for those who want to go beyond analytics.

8 Months 🖥 Online & Offline 🎓 Certificate Included 💼 Placement Assistance
Get Details on WhatsApp

What you'll master

Python — OOP, Pandas, NumPy, Matplotlib
Machine Learning — 20+ algorithms
Deep Learning & Neural Networks
Natural Language Processing
SQL, Power BI & Tableau
Statistics & Mathematics for DS
🕐
8 Months
Course Duration
👨‍💻
Online & Offline
Learning Mode
🏆
₹6 – 20 LPA
Average Salary
🚀
New Batch Soon
Limited Seats
10+
Tools & Libraries
3
Capstone Projects
9
Curriculum Modules
100%
Placement Assistance
Course Curriculum

What You'll Learn — Module by Module

An intensive 8-month program covering the full data science stack — from Python foundations to deployed ML models and BI reporting.

01
Python & Programming Foundations
Weeks 1–4  ·  4 weeks
+

Start with Python as a data science tool — not just a programming language. Learn OOP and data structures with a focus on real data problems.

Python Syntax & Data Types Functions & OOP List Comprehensions File I/O Pandas Basics NumPy Arrays Error Handling
02
Statistics & Mathematics for Data Science
Weeks 5–8  ·  4 weeks
+

The mathematical backbone of every ML algorithm. Understand why models work — not just how to run them — so you can tune and explain them in interviews.

Descriptive Statistics Probability & Distributions Linear Algebra Essentials Hypothesis Testing Bayesian Thinking Regression & Correlation
03
SQL & Data Engineering Basics
Weeks 9–11  ·  3 weeks
+

Data scientists spend 80% of their time preparing data. Master SQL to pull, clean, and structure data from databases before any model runs.

Advanced SQL Queries Window Functions CTEs & Stored Procedures Database Design ETL Concepts SQL + Python Integration
04
Exploratory Data Analysis & Feature Engineering
Weeks 12–13  ·  2 weeks
+

Build systematic EDA pipelines that reveal insights before modelling. Learn feature engineering techniques that directly improve model accuracy.

Missing Value Treatment Outlier Detection Feature Scaling Encoding Categorical Variables Correlation Analysis Seaborn & Matplotlib Plots
05
Machine Learning Algorithms
Weeks 14–19  ·  6 weeks
+

The core of the program. Learn 20+ supervised and unsupervised algorithms — understanding when to use each and how to evaluate and improve them.

Linear & Logistic Regression Decision Trees & Random Forest SVM & KNN Gradient Boosting / XGBoost K-Means Clustering PCA & Dimensionality Reduction Model Tuning & Cross-Validation Scikit-learn Pipelines
06
Deep Learning & Neural Networks
Weeks 20–23  ·  4 weeks
+

Move from classical ML to neural networks. Build CNNs for image classification and RNNs for sequential data using TensorFlow and Keras.

Artificial Neural Networks Activation Functions & Backprop Convolutional Neural Networks Recurrent Neural Networks Transfer Learning TensorFlow / Keras
07
Natural Language Processing
Weeks 24–26  ·  3 weeks
+

Work with text data — the fastest-growing source of business intelligence. Build sentiment analysers, text classifiers, and NLP pipelines.

Text Preprocessing & Tokenisation TF-IDF & Word Embeddings Sentiment Analysis Text Classification Named Entity Recognition NLTK & SpaCy
08
Power BI & Tableau for Data Scientists
Weeks 27–29  ·  3 weeks
+

Communicate model results and data insights to business stakeholders. Build executive dashboards that translate your technical work into decisions.

Power BI Desktop & DAX Data Modelling Tableau Desktop KPI Dashboards Storytelling with Data
09
Capstone Projects & Placement Prep
Weeks 30–36  ·  7 weeks
+

Three industry-grade projects, a polished portfolio, and intensive interview preparation to help you land a Data Scientist or ML Engineer role.

Customer Churn Prediction Image Classification (CNN) NLP Sentiment Analysis Resume & GitHub Portfolio ML Interview Q&A Prep Placement Drive Access
Tools & Technologies

Industry-Standard Tools You'll Use Daily

Every library and platform taught in this course is actively used in production data science teams.

🐍
Python
🧠
Scikit-learn
🔥
TensorFlow
🐼
Pandas
🔢
NumPy
🗄️
SQL Server
📊
Power BI
📉
Tableau
Is This Course For You?

Who Should Enroll

This program is designed for those who want to build intelligent systems — not just read dashboards.

⚙️
Engineering Graduates
B.Tech / M.Tech in CS, IT, ECE, or Mechanical — leverage your technical foundation for data science roles.
💼
Working Professionals (2–5 yrs)
Software engineers, testers, or analysts looking to move into data science and ML roles.
📊
Data / BI Analysts
Already in analytics but want to add ML, Python, and deep learning to become a Data Scientist.
🔬
Researchers & Academics
Those with a quantitative background looking to apply their skills in industry data science roles.
Career Outcomes

High-Impact Roles You Can Target

Data Science is the highest-growth field in tech. Our graduates step into well-paying, high-impact roles.

🤖 Data Scientist
₹8 – 20 LPA
Flipkart, Amazon, Google, Microsoft, Razorpay, CRED
⚙️ ML Engineer
₹10 – 20 LPA
Ola, Swiggy, Zomato, PhonePe, Meesho, InMobi
🧠 AI Engineer
₹10 – 18 LPA
TCS, Wipro, Infosys AI Labs, HCL, Tech Mahindra
📝 NLP Engineer
₹8 – 16 LPA
Freshworks, Zoho, Sarvam AI, Krutrim, Amdocs
🔍 Research Analyst
₹6 – 12 LPA
KPMG, EY, Deloitte, Boston Consulting Group, McKinsey
📊 Senior Data Analyst
₹7 – 14 LPA
Accenture, Cognizant, Genpact, Mphasis, Mu Sigma
Our students placed at
Student Stories

Our Students, Placed & Thriving

Real results from those who've completed the Data Science program.

DM
Deepak Mittal
Sr. Executive · Infopro Learning
★★★★★

My experience with The XL Academy is amazing. The ML modules were taught with incredible depth — every algorithm explained with real use cases, not just theory. Highly recommended.

PA
Purushottam Anand
MIS Executive · Max Life Insurance
★★★★★

The course structure — from Python to Machine Learning — was very logical. By the end I had 3 portfolio projects and the confidence to crack ML interviews.

AH
Abhishek H S
MIS Executive · Zepto
★★★★★

Moving from a software tester role to a Data Scientist felt impossible before this course. The placement team helped me land multiple interview calls within a month.

RT
Rameshwari Tailor
Trainee Operations · Spectrum
★★★★★

The faculty genuinely cares. Doubt-clearing sessions after every module meant I never got stuck. The deep learning project was my favourite part of the entire program.

Common Questions

Data Science with ML — FAQs

Is this course suitable for someone without a CS background?
Yes, but you need to be comfortable with basic mathematics and willing to invest time in learning Python from scratch. Engineering and science graduates without CS backgrounds do very well in this program.
What is the difference between Data Science and Data Analytics with Python?
Data Science covers ML, Deep Learning, NLP and model building. Data Analytics with Python focuses on analysis, dashboards, and reporting. If you want to build predictive models, choose Data Science. For business reporting and BI, choose Data Analytics.
Do I need to know Python before joining?
No. The program starts from Python fundamentals (Module 1) and builds up progressively. By week 4 you'll be comfortable enough to work on data problems in Python.
What projects will I build?
Three capstone projects: a customer churn prediction model (ML), an image classifier (CNN), and a sentiment analysis system (NLP). All three are portfolio-grade and frequently discussed in interviews.
How long does placement take after completion?
Most students who actively participate in placement drives receive their first offer within 30–60 days of completing the program. This depends heavily on interview preparation and resume quality, which we help with during Module 9.
Is EMI available for the course fee?
Yes, EMI options and education loan tie-ups are available. Contact our counsellors at +91 73036 09096 for a personalised fee and financing breakdown.

Ready to Become a Data Scientist?

Book a free demo class — experience our teaching style before you commit. New batch starting soon, limited seats.