Live online batches across IST, EST & GST — learners in 189+ countries
Home Courses Data Science AI Machine Learning Data Science certification Training
Data Science AI Machine Learning Upskill with BISP Powered By AI

Data Science certification Training

Learn Data Science with python to become a data scientist , in our professional training program to understand how to implement Data Science in various business scenarios with the help of project implementation using Python. We are startin…

4.8  ·  Rated by learners Certificate of completion
Duration
25 Hours
Mode
Live + Recorded
Level
Beginner → Pro
Language
English / Hindi

Course overview

About the Data Science certification Training program.

Learn Data Science with python to become a data scientist , in our professional training program to understand how to implement Data Science in various business scenarios with the help of project implementation using Python. We are starting from Introduction to data science, how data is important, how we can play with data including complete Data Science life cycle concepts from Data Collection, Data Extraction, Data Cleansing using Python , Data Exploration, Data Transformation, Data Mining, building Prediction models, Data Visualization, Statistical Analysis, Text Mining, Regression Modelling, Hypothesis Testing, Predictive Analytics, Machine Learning, Deep Learning, Neural Networks, Natural Language Processing, Predictive Modelling. You will be learn Data Manipulation, Data Analysis with Statistics Data Communication with Information in our Data Science certification training.

Why learn with BISP

Trusted by professionals across 30+ countries.

Industry trainers

Certified consultants with 12+ years of real project experience.

Hands-on practice

Real-time scenarios & live project modules, not just slides.

Placement support

Resume building, mock interviews & job referrals.

Certification

BISP certificate + full guidance for official exams.

Course curriculum

Designed by real-time industry professionals around current job roles.

Download curriculum (PDF)
17 modules 123 topics
01 Course overview

What is Data science?
Data science is a domain and it's a combination of expertise in programming, knowledge of mathematics and statistics to extract meaningful insights from given data of any Industry. And practitioners may apply ML algorithms to numbers, text, images, video, audio, and more that can perform tasks which generate insights that analysts and business users translate into tangible business value.

Why to learn data Science?
Data science continues to evolve as one of the most promising and in-demand career paths for skilled professionals. There is a growing need among companies for professionals to know ins and outs of Data Scientists. A successful data professionals can understand or to uncover useful intelligence for organizations. They  possess a level of flexibility and understanding to maximize returns at each phase of the process.

What Does a Data Scientist Do?
Data Scientist need to possess a strong quantitative background in statistics and linear algebra as well as programming knowledge with focuses in data warehousing, mining, and modeling to build and analyze algorithms. Leadership quality needed to deliver tangible results to various stakeholders across an organization or business. 

It's Really Good to Be a Data Scientist Right Now!
Data is the new corporate currency, as advancing impact on the data science sector is far-reaching and, as a result, a range of new roles and skill-set are in demand. The skills required as a data analyst, IT architect, test manager and data visualise are all required under the data science umbrella. The average salary for a data scientist was more than $111,000 in 2016, and the Bureau of Labour Statistics predicts that jobs in this field will grow by 11% by 2024

02 Acquire new skills with our Online Data Science Training Course 11 topics
  • Thorough knowledge of the statistical approach
  • Master in concepts of Predictive Analytics using Python, and how they relate to practical approach.
  • Machine Learning and how to Validate machine learning models
  • Experts in Data Visualization,
  • Gain practical knowledge over Big Data and Analytics, etc
  • Python
  • Perl
  • C/C++
  • SQL
  • Java
  • And python skills that are required to become a data scientist

Prerequisites
This training course does not presume or require any prior knowledge or prerequisites. However, basic knowledge would be an added advantageous. We are recommending,  knowledge of programming languages like...

03 Course Overview

If you want to accelerate your career with Data Science certification program, world class experienced Trainers and faculty. Encourage yourself and become to master in trending data scientist skills including statistics, hypothesis testing, data mining. We are covering clustering, decision trees, linear and logistic regression, data wrangling, data visualization, regression models, Hadoop, Spark, PROC SQL, SAS Macros, recommendation engine, supervised and unsupervised learning and more. Our certification Program covers online instructor-led training classes including a lot of case studies, real time project working, and machine learning working concepts, expert guidance for certification. After completion of training candidate has expertise over concepts, mathematical computing, SciPy package and its sub-packages such as Integrate, Optimize, Statistics, IO, and Weave, linear regression, logistic regression, clustering, dimensionality reduction, K-NN and pipeline. Mastering in concepts of recommendation engine, time series modeling, practical mastery over principles, algorithms and more..

04 Introduction to Data Science 4 topics
  • What is Data Science?
  • Data Scientists
  • Examples of Data Science
  • Python for Data Science
05 Data Analytics Overview 7 topics
  • Data Visualization
  • Processes in Data Science
  • Data Wrangling, Data Exploration, and Model Selection
  • Exploratory Data Analysis or EDA
  • Data Visualization
  • Plotting
  • Hypothesis Building and Testing
06 Statistical Analysis and Business Applications 10 topics
  • Introduction to Statistics
  • Statistical and Non-Statistical Analysis
  • Some Common Terms Used in Statistics
  • Data Distribution: Central Tendency, Percentiles, Dispersion
  • Histogram
  • Bell Curve
  • Hypothesis Testing
  • Chi-Square Test
  • Correlation Matrix
  • Inferential Statistics
07 Python: Environment Setup and Essentials 13 topics
  • Introduction to Anaconda
  • Installation of Anaconda Python Distribution - For Windows, Mac OS, and Linux
  • Jupyter Notebook Installation
  • Jupyter Notebook Introduction
  • Variable Assignment
  • Basic Data Types: Integer, Float, String, None, and Boolean; Typecasting
  • Creating, accessing, and slicing tuples
  • Creating, accessing, and slicing lists
  • Creating, viewing, accessing, and modifying dicts
  • Creating and using operations on sets
  • Basic Operators: 'in', '+', '*'
  • Functions
  • Control Flow
08 Mathematical Computing with Python (NumPy) 10 topics
  • NumPy Overview
  • Properties, Purpose, and Types of ndarray
  • Class and Attributes of ndarray Object
  • Basic Operations: Concept and Examples
  • Accessing Array Elements: Indexing, Slicing, Iteration, Indexing with Boolean Arrays
  • Copy and Views
  • Universal Functions (ufunc)
  • Shape Manipulation
  • Broadcasting
  • Linear Algebra
09 Scientific computing with Python (Scipy) 8 topics
  • SciPy and its Characteristics
  • SciPy sub-packages
  • SciPy sub-packages –Integration
  • SciPy sub-packages – Optimize
  • Linear Algebra
  • SciPy sub-packages – Statistics
  • SciPy sub-packages – Weave
  • SciPy sub-packages - 10
10 Data Manipulation with Python (Pandas) 9 topics
  • Introduction to Pandas
  • Data Structures
  • Series
  • DataFrame
  • Missing Values
  • Data Operations
  • Data Standardization
  • Pandas File Read and Write Support
  • SQL Operation
11 Machine Learning with Python (Scikit–Learn)- Overview 12 topics
  • Introduction to Machine Learning
  • Machine Learning Approach
  • How Supervised and Unsupervised Learning Models Work
  • Scikit-Learn
  • Supervised Learning Models - Linear Regression
  • Supervised Learning Models: Logistic Regression
  • K Nearest Neighbors (K-NN) Model
  • Unsupervised Learning Models: Clustering
  • Unsupervised Learning Models: Dimensionality Reduction
  • Pipeline
  • Model Persistence
  • Model Evaluation - Metric Functions
12 Natural Language Processing with Scikit-Learn- Overview 14 topics
  • NLP Overview
  • NLP Approach for Text Data
  • NLP Environment Setup
  • NLP Sentence analysis
  • NLP Applications
  • Major NLP Libraries
  • Scikit-Learn Approach
  • Scikit - Learn Approach Built - in Modules
  • Scikit - Learn Approach Feature Extraction
  • Bag of Words
  • Extraction Considerations
  • Scikit - Learn Approach Model Training
  • Scikit - Learn Grid Search and Multiple Parameters
  • Pipeline
13 Data Visualization in Python using Chart JS 1 topics
  • Introduction to Data Visualization
14 â–º ChartJS 9 topics
  • Libraries
  • Chart JS Features
  • Labels
  • Data
  • Datasets
  • Controlling Line Patterns and Colours
  • Set Axis, Labels, and Legend Properties
  • Annotation
  • Different Types of Charts
15 Data Science with Python Web Scraping- Overview 11 topics
  • Web Scraping
  • Common Data/Page Formats on The Web
  • The Parser
  • Importance of Objects
  • Understanding the Tree
  • Searching the Tree
  • Navigating options
  • Modifying the Tree
  • Parsing Only Part of the Document
  • Printing and Formatting
  • Encoding
16 Student Take away 3 topics
  • Study Material
  • Learning stuff
  • Sample project for practice
17 Class Delievery 1 topics
  • Live Interactive classes with expert

Delievery  Methodology
We are using an experiential delievering methodology that blends theoretical concepts with hands-on practical learning to ensure a holistic understanding of the subject or course

Course details

Who it is for, what you need, and how it is delivered.

Who should learn Data Science certification Training?
  • Any IT experienced Professional
  • Who wants to make a career in python web development
  • Software automation
  • Data Analytics
  • Fresh Graduates
  • Any B.E/ B.Tech/ BSC/ MCA/ M.Sc Computers/ M.Tech/ BCA/ B.Com College Students in any stream
Prerequisites

PREREQUSITE
This certification training course does not presume or require any prior knowledge on Python for Data Science. 
To understand the concepts, useful to know basic knowledge of application. We are recommending that students have following:

  • Basic understanding of Computer Programming Languages
Delivery methodology

We are using an experiential delivering methodology that blends theoretical concepts with hands-on practical learning to ensure a holistic understanding of the subject or course.

Class delivery

Live Interactive classes with expert

Certificate of completion

Earn an industry-recognised BISP Trainings certificate when you finish the course.

BISP Trainings Certificate of Completion
  • Verifiable certificate with a unique ID
  • Shareable on LinkedIn & your resume
  • Recognised by our hiring partners

Upcoming batches

Reserve your seat for the next live session.

SessionDateTimeReserve
D 18 Sep 2026 (Fri) 07:00 Reserve seat →
R 21 Sep 2026 (Mon) 08:00 Reserve seat →

Frequently asked questions

Everything you need before you enroll.

Can I attend a demo session before enrollment?

Yes. You may attend a demo class before enrollment for training quality evaluation, and interact one-to-one with the trainer for any specific requirement.

Can you schedule training as per my availability?

Yes. We discuss it with the trainer and schedule the training at a convenient time for you.

What if I miss a class?

You get the recorded session. You may also retake the whole training multiple times within a 6-month period with the same trainer.

Is there live project training?

Yes. The curriculum includes real-time scenarios and live project modules, with the trainer explaining every topic end-to-end.

How can I pay for the course?

Enroll securely via the payment gateway on this page using card, UPI or net-banking. EMI options are available.

More queries?

Call us at +91 769-409-5404 & +1 678-701-4914, or write to support@bisptrainings.com.

Case studies & learning PDFs

Free Data Science AI Machine Learning resources to explore.

Relevant courses

Learners who took this also explored these.

Not sure if this course is right for you?

Book a free 1-on-1 counselling call and get a personalised learning roadmap.

Book free trial →