Data Science and Machine Learning with Python

With the help of our extensive Data Science and Machine Learning course, turn unprocessed data into useful insights. This practical curriculum, which builds your knowledge from the bottom up, integrates statistical analysis, programming, and AI basics, making it ideal for aspiring data professionals.

40 hours of live instructor-led training
Hands-on projects with real datasets
Industry-relevant case studies
Interactive coding sessions
Advanced analytics techniques
Career guidance and portfolio building

Refer & Earn | Share:

Accreditations

Data Science and Machine Learning with Python Course Overview

This course covers Introduction to Data Science, Data Mining and Machine Learning, Their Applications, Future Scope, Data Science Process Flow, Statistics, Predictive Analytics, Classification, Clustering, Regression, Exploratory Data Analysis, Machine Learning Algorithms such as Linear Regression, Logistic Regression, KNN, Naive Bayes, Decision Trees, Random Forest, and Evaluation Metrics. Text mining, text analytics, and an introduction to natural language processing are also covered. POS Tagger, NER Tagger, and TF-IDF are some of its uses. All principles are implemented practically in Python. Resolving end-to-end data science issues and business use cases.

Data Science and Machine Learning with Python Key Highlights

Get Practical Hands-on Python with Machine Learning
Learn Business Use cases
Discussion on Features for different problems
Hands-on TF-IDF implementation
Implementation of Text Mining in Python

Curriculum

Introductory Session

Analytics Buzzwords – Data Science, Big Data, Analytics, BI, Machine Learning, Hadoop
Applications of Data Science / Usage of Data Science
Real-Life Examples
Future of Data Science in terms of Job Opportunities
Comparison of Job Role in Data Science
Data Science Process Flow (Descriptive, Predictive, Prescriptive)

Data Science Technology Stack - Python & R

Introduction to Python for Data Science
Python Basics
Python Lists
Python Functions and Packages
Python NumPy
Hands-on Python -Importing various data science packages

Introduction to Machine Learning

Applications of Machine Learning
Types of Machine Learning (Supervised & Unsupervised)
Problem Identification – Classification & Clustering
Approach to Solving Data Science Problem
Introduction to Python with Machine Learning
Introduction to Python for Data Analysis
Python Libraries and Data Structures for Data Science

Exploratory Data Analysis using Pandas

Practical – Hands-on Python with Machine Learning
Univariate Analysis
Bivariate Analysis
Scatterplot, Barplot, Boxplot
Outliers Detection
Data Preprocessing – Handling Missing Values, Outliers, Data Cleaning

Statistics for Data Science

Gaussian Distribution
Correlation and Covariance
Hypothesis Testing
Feature Engineering

Introduction to Machine Learning Algorithms

Regression Vs Classification
Linear Regression, Logistic Regression, KNN, Naive Bayes
Tree Based Modelling Algorithms – Decision Trees, Random Forest, Ensemble, Bagging, Boosting
Cross Validation
Evaluation Metrics – RMSE, Accuracy, Confusion Matrix, ROC
Implementation of ML Algorithms in Python

Introduction to Unsupervised Learning

Introduction to Clustering
K-means Clustering
Implementation of K-means clustering in Python

Introduction to Natural Language Processing

Introduction to Text Analytics
Steps of Text Mining
POS Tagging
NER Tagger
TF-IDF Model

Implementation of NLP in Python

TF-IDF implementation
Implementation of Text Mining in Python

Solving end-to-end data science problems

Business Use cases
Discussion on Features for different problems

Enquiry for Corporate Training

"*" indicates required fields

Name*

First Last

Comments

This field is for validation purposes and should be left unchanged.

Our Esteemed Partners

Who can attend?

This course is ideal for:

Software Engineers and Developers
Business and Data Analysts
Statisticians and Mathematicians
Domain Experts
IT Professionals

Software Engineers and Developers
Business and Data Analysts
Statisticians and Mathematicians
Domain Experts
IT Professionals

Software Engineers and Developers
Business and Data Analysts
Statisticians and Mathematicians
Domain Experts
IT Professionals

Training Schedule

Contact Course Advisor

Interested in AgileFever offerings? Message us now and we will reach out to you!

Send a Message

Enquiry for Corporate Training

"*" indicates required fields

Name*

First Last

Name

This field is for validation purposes and should be left unchanged.

Exam & Certification

Exam Details

Name of Exam – AgileFever Data Science and Machine Learning with Python Examination

Exam details are as follows:

Practical Exams, Lab Assessments, and Projects at the end of every completed module.
Capstone Project at the end of the 40-hour training.

Prerequisites

Anyone can register to this course.

Benefits

Corporate Benefits

Build internal expertise and reduce external costs.
Solve business problems with advanced analytics.
Use data science for competitive advantage.
Improve outcomes through data-driven decision-making.
Upskill workforce with modern technical tools.

Individual Benefits

Master data science for higher tech salaries.
Create real projects for your portfolio.
Learn complete data science workflow skills.
Get hands-on experience with business cases.
Enter a fast-growing field with high demand.

Certification Process

Step 1: Register for the Data Science and Machine Learning with Python with AgileFever

Step 2: Attend Agile Fever’s 40 hours of training

Step 3: Upon successful completion of the course, you will receive certification from AgileFever

Contact Course Advisor

Interested in AgileFever offerings? Fill out this form and we will reach out to you!

Your Name(Required)

First Last

Phone

Hidden

Interested Course

Hidden

What's on your mind?

Please let us know what's on your mind. Have a question for us? Ask away.

Your Comments/Questions(Required)

Name

This field is for validation purposes and should be left unchanged.

Testimonials

The Data Science and Machine Learning course from Agilefever was fantastic! The trainers were very knowledgeable and provided detailed explanations with real-world examples. The course covered everything from Python basics to advanced machine-learning techniques. The certification has added great value to my resume, and I’m already using these skills at work.

I had an amazing experience with Agilefever’s Data Science and Machine Learning with Python training! The course was well-structured, and the instructors simply explained complex concepts. The hands-on projects were a game-changer, helping me apply what I learned in real-world scenarios. After completing the certification, I feel much more confident in my data science skills. Highly recommend it!

empty

What is data science and machine learning with python course?

It’s like learning to be a data detective using Python, where you discover hidden patterns in information and teach computers to make smart guesses. You learn to work with numbers, make charts, and solve real-world problems using computer programs.

How many hours is data science and machine learning with python course?

40 hours.

Which is the best institute for data science and machine learning with python training?

According to the reviews and ratings, we can suggest AgileFever’s training program.

What is data science and machine learning in Python?

Data science is like being a number detective – you look at lots of information to find useful answers. Machine learning is teaching computers to learn from examples, like teaching a computer to recognize cats in pictures after showing it many cat photos.

Which is better, AI/ML or data science?

It’s like asking whether being a chef or a restaurant manager is better – they’re different but related jobs. Data science helps understand information, while AI/ML focuses on making smart computer programs – choose based on what interests you more.