Data Science and Business Analytics

Beginner to Mastery

Applied Data Science with Python

Cutting-edge Data Science Tools.

Comprehensive curriculum covering Python, statistics, machine learning, and deep learning.

Strong emphasis on practical application through hands-on projects.

Flexible program design to accommodate learners from diverse backgrounds.

Group Enrollment with Friends or Colleagues

Applied Data Science with Python

Course Duration

240 Hours

Next Batch

14 September 2025

Course Material

Live. Online. Interactive.

Cutting-edge focus on deep learning for AI proficiency.

Equip graduates with in-demand skills for successful careers in data science.

Industry-relevant case studies to bridge the gap between theory and real-world problem-solving.

Work on real-world projects and case studies to apply concepts practically and build a strong portfolio.

Highlight Applied Data Science with Python

KEY HIGHLIGHTS OF APPLIED DATA SCIENCE WITH PYTHON PROGRAM

  • 25 + live session Across 4 month
  • 75 Hours of Self Paced Learning
  • Weekly sessions with industry professionals
  • Dedicated Learning Management Team
  • 240 hours of hands-on learning experience
  • 75+ Live Sessions Across 11 months
  • 105 Hours of Self-Paced Learning
  • Learn from Industry Experts.
  • More than 25+ industry-related projects and case studies
  • One-on-One with Industry Mentors
  • 24*7 Support
  • Dedicated Learning Management Team
  • 1:1 Mock Interview
  • No-Cost EMI Option
  • Designed for both working professionals and fresh graduates
  • High Demand and Career Opportunities
  • Competitive Edge and Innovation
  • Problem-Solving and Critical Thinking

WHY JOIN APPLIED DATA SCIENCE WITH PYTHON PROGRAM?

High Demand

Skills in Python, data analysis, and machine learning are highly sought after and lead to well-paying careers in tech, finance, and healthcare.

Versatility and Practical Application

This program’s skills offer flexibility, allowing you to excel in roles like data analyst, software developer, or AI researcher.

Competitive Edge and Innovation

Learning these tools gives you a competitive edge, sharpens analytical skills, and enables innovation in AI and intelligent systems.

Problem-Solving and Critical Thinking

It sharpens problem-solving and critical thinking by using statistics and machine learning for data-driven decision-making.

UPCOMING BATCH:

14 September 2025

SkillzRevo

SkillzRevo Solutions

30 MINUTE MEETING

Web conferencing details provided upon confirmation.

Corporate Training, Enterprise training for teams

Batch schedule

BatchBatch Type
Online Live Instructor Led SessionFull-Time
Online Live Instructor Led SessionPart-Time

Regional Timings

BatchBatch Type
IST (India Standard Time)09:00 PM–12:00 AM
Bahrain, Qatar, Kuwait, Saudi Arabia06:30 PM–09:30 PM
UAE / Oman07:30 PM–09:00 PM

Applied Data Science with Python OVERVIEW

This program is designed to equip students with the fundamentals required in data science, as it has become one of the most promising fields nowadays. Learning Python programming helps to learn how data can be manipulated, analysed, and visualised using the same program. Knowing the statistics, you can use it to see how things stack up, what inferences you could derive from them, and base your decisions on data as opposed to gut. From there, the curriculum reaches out to machine learning and deep learning so that students can equip intelligent systems capable of predicting from data. About the course, This extensive program caters to prospective data scientists, analysts, and machine learning engineers in exploring their abilities and assisting them derive meaningful information from diverse datasets..

ENROLL NOW & BOOK YOUR SEAT AT FLAT 50% WAIVER ON FEE

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Applied Data Science with Python Objectives

This course assures students that they will be competent in Python programming including Deep Learning, Machine Learning, and Statistics. Firstly, this will start with Python Programming where the student must learn how to write codes effectively as well as become conversant with libraries and frameworks for data analysis as well as scientific computing. The statistical segment of this program will also help them learn more about data distribution, probability theory, hypothesis testing, and regression analysis on which to base their factual decision-making. They should be ready now to understand machine learning such as supervised and unsupervised learning methods; model evaluation; and feature engineering so that they can build predictive models to identify patterns within complex datasets. This is followed by deep learning in neural networks such as convolutional or recurrent neural networks and their applications in image recognition and speech recognition among others. By the end of the course, the learners are expected to implement a Data Science project from scratch until it is designed according to contemporary practices thus converting raw information into action-oriented results.

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Why Learn Applied Data Science with Python ?

Master Essential Tools

Learn Python programming, data manipulation in Pandas and NumPy, and statistical analysis tools to explore the dataset and derive insights from it.

Build Predictive Models

Making machines helping to make decisions and predictions using Machine Learning & Deep learning techniques.

Unlock Data Potential

Discover hidden patterns and insights within your data through data analysis and feature engineering, driving informed decision-making.

Enhance Communication

Innovative ways of communicating detailed understanding and findings with data visualisation techniques.

Advance Your Career

Gain skills that can lead you to top jobs in data science, machine learning, and artificial intelligence.

Drive Innovation

Develop cutting-edge technologies and solutions with deep understanding of these tools.

Hands-On Learning

Work on real-world projects and case studies to apply concepts practically and build a strong portfolio.

Problem-Solving Mindset

Develop analytical and critical thinking skills to tackle complex business and research challenges using data-driven approaches.

Program Advantages

Covers Python, statistical analysis, machine learning, and deep learning for a broad data science foundation.

Focuses on current tools and practices to ensure up-to-date training.

Combines theory with projects for hands-on problem-solving skills.

Taught by knowledgeable educators with a focus on individual student attention.

Prepares students for roles like Data Analysts, Machine Learning Engineers, and AI Specialists.

Teaches state-of-the-art libraries and frameworks such as TensorFlow and Keras.

Develops problem-solving abilities and data-driven decision-making.

Encourages teamwork, idea sharing, and networking among students.

Helps students build a professional portfolio for job searches and promotions.

Provides a solid foundation for continuous learning in evolving data science technologies.

Description

Applied Data Science with Python program Certifications

NASSCOM

NASSCOM

Course Completion

Course Completion

Project Completion

Project Completion

Applied Data Science with Python Curriculum

Lecture 01: Introduction to Python
Lecture 02: Operators and Conditional Statements
Lecture 03: Lambda Functions, *args, **kwargs, Functions
Lecture 04: Data Structures - List, Tuple, and List Comprehensions
Lecture 05: Data Structures - Set and Dictionaries
Lecture 06: Classes, Objects and Constructors, Inheritance
Lecture 07: Polymorphism, Abstraction and Encapsulation
Lecture 08: Connecting to Databases
Lecture 09: Introduction to Numpy and Pandas
Lecture 10: Introduction to Seaborn and Matplotlib
Lecture 11: Introduction to Statistics, Descriptive Statistics, Sample, Population, Major of Central Tendency, Standard Deviation,
Lecture 12: Variance, Range, IQR, Outliers, Correlation, Covariance Skewness, Kurtosis, Probability
Lecture 13: Probability, Probability distributions, Central Limit Theorem, Binomial and Poisson Distribution
Lecture 14: Normal Distribution, Type I & Type II Error
Lecture 15: T-test, Z-test, Hypothesis Testing
Interview Questions
Lecture 16: Introduction to ML, Types of variables, Encoding, Normalization, Standardization, Types of ML, Linear Regression
Lecture 17: Linear Regression, Logistic Regression, SVM, KNN, Naïve Bayes, Decision Tree, Random Forest
Lecture 18: Mean Absolute Error, Mean and Root Mean Square Error, Confusion Matrix, R2 Score, Adjusted R2 Score,F1 Score
Lecture 19: Classification Report, AUC ROC, Accuracy, Ensemble Techniques, Random Forest, Xgboost
Lecture 20: Unsupervised Machine Learning, PCA, Clustering, k-Means Clustering and Hierarchical clustering
Lecture 21: Introduction to Neural Network, Foreward Propagation, Activation Function
Lecture 22: Activation Function(Linear, Sigmoid, Relu, Leaky Relu), Optimizers, Gradient Descent, Stochastics Gradient Descent
Lecture 23: Mini batch Gradient Descent, Adagrad, Padding, Pooling, Convolution, Checkpoints and Neural Networks Implementation
Lecture 24: Introduction to Time Series Analysis, Various components of the TSA, Decomposition Method (Additive Method and Multiplicative)
Lecture 25: ARMA and ARIMA
Lecture 26: Project Session

Applied Data Science with Python Skills Covered

Data Analysis
Data Manipulation
Statistical Analysis
Data Visualization
Machine Learning
Model Evaluation
Feature Engineering
Neural networks
Transfer learning
Deep Learning
Computer Vision techniques
Image Processing
Text Processing
Sentiment Analysis
Language Modelling
Machine Learning
Deep Learning
Data Analysis
Data Visualization

Applied Data Science with Python Tools Covered

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Applied Data Science with Python Program Benefits

Applied Data Science with Python Program Benefits Illustration

CAREER OPPORTUNITIES AFTER THIS COURSE

Machine Learning Engineer Salary Range

Min

$90,000

Average

$120,000

Max

$150,000

Projects

MASTER GANS, TRANSFORMERS & DEEP LEARNING WITH REAL PROJECTS

Practice Essential Tools

Designed By Industry Experts

Get Real-world Experience

Machine Learning
NO. OF PROJECTS: 10
Deep Learning
NO. OF PROJECTS: 10

Capstone Projects of this Program

Multimodal Text-to-Image Generator

A system that creates high-quality, realistic images from descriptive text inputs, blending multiple data types for creative visual output.

AI Music Composer with Genre Adaptation

An AI tool that generates original musical compositions while adapting to specific genre styles, tempo, and mood preferences.

Realistic Deepfake Video Synthesizer

A tool that realistically manipulates and synthesizes video content to create authentic-looking deepfake footage for various applications.

Personality-Driven Conversational AI Assistant

A chatbot designed to interact with a distinct and consistent personality, providing a more natural and engaging user experience.

Artistic Style Transfer Engine for Videos

A program that applies the artistic style of a source image to every frame of a video, creating a new, stylized visual experience.

Context-Aware Text Summarization System

An advanced system that generates concise summaries of long texts by understanding the document's broader context and key information.

Voice Cloning and Speech Style Transfer Tool

A tool that replicates a speaker's voice and transfers a specific speech style or emotion to new synthesized audio content.

Interactive AI Storyteller with Image Generation

An AI that collaboratively creates stories with users, dynamically generating scenes and characters based on a developing narrative.

2D Sketch to 3D Object Generation Pipeline

A seamless workflow that converts simple two-dimensional sketches into detailed, three-dimensional models for creative and design purposes.

Synthetic Data Generator for Model Training

A system that produces large and diverse datasets for machine learning models, overcoming data scarcity for effective training.

AI-Powered Video Subtitle Generator and Translator

An automated solution that transcribes spoken language in videos and translates it into accurate subtitles for global accessibility.

Generative Design Tool for Product Prototyping

An AI application that rapidly generates numerous product design prototypes based on a set of constraints and functional requirements.

RAG-based Research Assistant (Retrieval-Augmented Generation)

An intelligent assistant that answers complex queries by retrieving relevant information from large documents and generating coherent responses.

Multilingual Chatbot with Memory and Personality

A conversational agent that can communicate in multiple languages while maintaining a consistent personality and recalling past interactions.

AI-Powered Comic Strip Generator from Text Prompts

A tool that creates unique comic strips by converting user text prompts into sequential images with a consistent artistic style.

Explainable AI Engine for Text Classification

An AI system that classifies text and provides clear, understandable reasons for its decisions, ensuring transparency and trust.

Autonomous Slide Generator from Research Papers

An AI that automatically extracts key findings and data from research papers to create well-structured, presentable slide decks.

AI Assistant for Code Generation and Explanation

A helpful tool that writes code snippets and explains complex programming logic in simple terms, assisting developers with their tasks.

AI-Driven Marketing Content Generator Across Formats (text, image, video)

A unified platform that produces marketing materials in various formats, including text, images, and videos, from a single campaign brief.

Real-Time Emotion Detection and Response AI System

A system that identifies human emotions from facial expressions or speech and generates appropriate, empathetic responses in real time.

Job Obligation After This Course

WE CAN APPLY FOR JOBS IN

Preparing the Data for acquisition

cleaning, transformation, exploration and analysis.

Building, training, and evaluating statistical and machine learning models for predictive and prescriptive analytics.

Applying deep learning, natural language processing, and computer vision techniques for complex problem-solving.

Creating compelling visualizations and communicating insights effectively to technical and non-technical audiences.

Stay updated with the latest advancements in AI and apply them to improve existing solutions.

Applying data-driven solutions to address business challenges and identify new opportunities.

Troubleshoot and resolve issues related to AI models and systems.

Working effectively with cross-functional teams to achieve project objectives.

Companies Hiring for this Course

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Admission Process

The application process consists of three simple steps. An offer of admission will be made to selected candidates based on the feedback from the interview panel. The selected candidates will be notified over email and phone, and they can block their seats through the payment of the admission fee.

Course Fees & Financing

Course Fees

Enroll Now & Save Up To

60%

In USD

$1,049

In INR

84,999

Inclusive of All Taxes

Enroll Now →
Payment Partners

We partnered with financing companies to provide competitive finance options at 0% interest rate with no hidden costs.

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UPCOMING BATCHES/PROGRAM COHORTS

BatchDateTime (IST)Batch Type
Online Live Instructor Led Session30 August 20259 PM to 12 AMBatch 1
Online Live Instructor Led Session14th Sept 20259 PM to 12 AMBatch 2

COMPARISON WITH OTHERS

FeatureOur CourseCOMPETITOR ACOMPETITOR B
Curriculum ScopeComprehensive: Python, ML, DL, NLP, CV, Generative AIBasic ML and DL focusGeneral AI with less focus on Generative AI
Hands-On ExperienceExtensive practical projects with tools like GPT, DALL-E 2Limited practical projectsHands-on projects mainly in traditional AI
Advanced ToolsGPT, DALL-E 2, Midjourney, Hugging Face, Transformers, GANs, RAG, LangChainFocus on traditional ML frameworksEmphasis on standard ML and AI tools
Instructor ExpertiseExperienced professionals with industry and research backgroundMix of industry and academic instructorsPrimarily academic-focused instructors
Real-World ApplicationsEmphasis on real-world problem-solving and innovationMostly theoretical applicationsGeneral applications with less focus on innovation
Career SupportStrong focus on career advancement and networkingBasic career servicesLimited career support and networking opportunities
Networking OpportunitiesConnect with peers and industry leadersLimited networking eventsFew networking opportunities
Certification ValueRecognized certification for advanced AI rolesStandard certificationGeneral certification with less industry recognition

Frequently Asked Questions