PRO
Hands-On Data Science Using Python
Hands-On Data Science Using Python
Learn data science using Python with developing strong data science skills. Gain hands-on experience in data manipulation, probability distributions, EDA, ML algorithms and model evaluation for practical data-driven insights.
Become a skilled professional
Learn from the best
Taught by top faculty & industry experts
Learn by doing
Apply skills with guided projects and interactive coding exercises
Mock Interview
Guided Projects
Coding Exercises
Learn with AI
Get AI-powered coding hints & instant doubt resolution
24x7 Doubt resolution
Coding Hints
Course outline
Industry focussed curriculum designed by experts
Introduction to NumPy
7 items
0.28 hr
- Introduction to Numpy
- Indexing an Array
- Slicing an Array
- Operations on an Array
- Arithmetic Functioning in Numpy
- Concatenation of Array
- Splitting of Array
Introduction to Pandas
7 items
1.05 hr
- Introduction to Pandas
- Introduction to Data Structures
- Introduction to Pandas Series and Creating Series
- Manipulating Series
- Introduction to Dataframes and Creating Dataframe
- Manipulating the Dataframes
- Reading Data From Different Sources
Introduction to Probability and Distributions
7 items
1.08 hr
- Probability - Meaning and concepts
- Rules for Computing Probability
- Marginal Probability and Example
- Bayes theorem and Example
- Binomial Distribution and Example
- Normal Distribution and Example
- Poisson Distribution and Example
Introduction to Descriptive Statistics
19 items
2.23 hr
- Statistical Learning Outline
- Why Statistics and Big Data
- Statistics Methods
- Classical Definition and Definition of Stats
- Some Vital Terms in Stats
- Sources and Types of Data, Data Sets
- Data Objects, Attributes and Attribute Types
- Statistical Learning Summary
- Data and Histogram
- Descriptive Statistics Outline
- Central Tendency and 3 Ms
- Measures of Dispersion, Range, IQR
- Standard Deviation
- Coefficient of Variation
- The Empirical Rule and Chebyshev Rule
- Five Number Summary and the Boxplot along with Other Plots
- Data Visualizations
- Correlation Analysis
- Summary - Descriptive Statistics
Introduction to Exploratory Data Analysis (EDA)
10 items
1.40 hr
- Introduction to EDA
- Descriptive Data Measures
- 5 Point Summary and Skewness of Data
- Box-plot, Covariance and Coeff of Correlation
- Let's Get Our Hands Dirty with Code
- Univariate and Multivariate Analysis
- Encoding Categorical Data
- What is Preprocessing?
- Imputing Missing Values
- Working with Outliers
Supervised Learning - Linear Regression
4 items
1.06 hr
- Concepts of Machine Learning and Importance
- Supervised Machine Learning - Introduction
- Linear Regression and its Pearson’s Coefficient
- Linear Regression Mathematically and Coefficient of Determinant
Supervised Learning - Logistic Regression
2 items
0.43 hr
- Classification Algorithm - Logistic Regression
- Logistic Regression Model and Sigmoid Function
Introduction to Decision Trees
1 item
0.51 hr
- Decision Trees - Introduction
Introduction to Ensemble Techniques
8 items
1.08 hr
- Ensemble Methods
- Bagging
- Bagging - Hands on Exercise
- Boosting
- Types of Boosting
- Adaboosting - Hands on Exercise
- Gradient Boosting - Hands-on Exercise
- Random Forest
Introduction to Unsupervised Learning
3 items
0.37 hr
- Introduction to Unsupervised Learning - Clustering
- Clustering - Types and Distance
- K-means Clustering
Guided Projects
Solve real-world projects with a step-by-step guide, starter code templates, and access to model solutions to boost your skills and build a standout resume.
- GUIDED PROJECT 1
- Exploratory Data Analysis on Movielens dataset
- In this project, we will dive into the MovieLens dataset, a rich collection of user ratings, movie information, and genres. Our objective is to perform a thorough analysis of the data, uncover key insights, and present these findings through visually compelling charts.
Course Instructors
Prof. Mukesh Rao
Senior Faculty, Academics, Great Learning
Prof. Mukesh Rao
Senior Faculty, Academics, Great Learning
Dr. Abhinanda Sarkar
Senior Faculty & Director Academics, Great Learning
Dr. Abhinanda Sarkar
Senior Faculty & Director Academics, Great Learning
Key highlights of our pro courses
Self-paced learning for your convenience
Comprehensive short courses with industry-relevant curriculum
Learn foundation to intermediate level skills
Hands-on guided projects and interactive coding exercises
Get recognised with a certificate of completion
AI support for interactive learning & mock interviews
Earn a certificate and verify your skills
Stand out to recruiters
Share on professional channels
Globally recognised
Land your dream job
Application-driven learning to
Become a Skilled Professional with Pro Courses
Gain work-ready skills with guided projects, top faculty and AI tools, all at an affordable price.
.jpg)
.jpg)
.png)
 (1).jpg)
Advance your career with
Top University programs
Gain industry-relevant skills through learning from top faculty, guidance from industry mentors, and hands-on projects.
UNIVERSITY
UNIVERSITY
MIT Professional Education
12 Weeks • Online
UNIVERSITY
UNIVERSITY
UNIVERSITY
McCombs School of Business at The University of Texas at Austin
7 months • Online
UNIVERSITY
McCombs School of Business at The University of Texas at Austin
7 months • Online
UNIVERSITY
McCombs School of Business at The University of Texas at Austin
6 months • Online
UNIVERSITY