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Data Science Mastery
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Data Science Mastery

Build a future-proof career with our industry-driven data science course. This hands-on program takes you from beginner to advanced levels and prepares you for top-tier jobs with a recognized data scientist certification course.

Level : Intermediate

Duration :180 hrs

Rating : 4.9/5

Language : Python

Activate this Course for :

₹ 21999
21999
50% Offer

Activate this Course for :

₹ 22999
22999
50% Offer
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Learn this Course

21999

₹21999

22999

₹22999

Data Science Mastery Course Overview

Analyze and visualize data using Python, Pandas, and Matplotlib

Work with machine learning algorithms for classification, regression, and clustering

Build data models, evaluate performance, and deploy solutions

Apply concepts in AI, deep learning, and big data

Get job-ready with resume support, interview prep, and capstone projects

Data Science Mastery Course Includes

Certification After completing the courses

We Provides 24/7 Dedicated Forum Support

Accessing to AI tools to enhance coding skills

Enjoy Lifetime access to course materials

Assessments to track your progress

Data Science Mastery Course Contents

  1. 1.1.What is Data Science?

  2. 1.2.Lifecycle of Data Science Projects

  3. 1.3.Applications and Use Cases

  4. 1.4.Roles: Data Analyst vs Scientist vs Engineer

  1. 2.1.Python Refresher (Data types, Loops, Functions)

  2. 2.2.List Comprehensions

  3. 2.3.Working with Jupyter Notebooks

  4. 2.4.Importing Libraries

  1. 3.1.Creating and Manipulating Arrays

  2. 3.2.Array Indexing and Slicing

  3. 3.3.Broadcasting and Vectorization

  4. 3.4.Mathematical Operations with NumPy

  1. 4.1.DataFrames and Series

  2. 4.2.Reading and Writing CSV/Excel Files

  3. 4.3.Filtering, Sorting, GroupBy

  4. 4.4.Handling Missing Data

  1. 5.1.Line, Bar, Pie, Histogram Plots

  2. 5.2.Customizing Plots

  3. 5.3.Seaborn: Countplot, Boxplot, Heatmap

  4. 5.4.Visual Data Analysis

  1. 6.1.Handling Duplicates and Missing Values

  2. 6.2.Data Transformation

  3. 6.3.Feature Scaling and Encoding

  4. 6.4.Outlier Detection

  1. 7.1.Univariate, Bivariate, Multivariate Analysis

  2. 7.2.Correlation Matrix and Pair Plots

  3. 7.3.Statistical Summaries

  4. 7.4.EDA Reporting

  1. 8.1.Descriptive Statistics

  2. 8.2.Probability Distributions

  3. 8.3.Sampling Techniques

  4. 8.4.Inferential Statistics (Hypothesis Testing)

  1. 9.1.Linear Algebra for Data (Vectors, Matrices)

  2. 9.2.Calculus Basics

  3. 9.3.Matrix Multiplication and Operations

  4. 9.4.Gradient Concept for ML

  1. 10.1.Types of ML: Supervised, Unsupervised, Reinforcement

  2. 10.2.Steps in Model Building

  3. 10.3.Overview of Training and Testing

  1. 11.1.Linear Regression, Polynomial Regression

  2. 11.2.Evaluation Metrics: MAE, MSE, RMSE, R2

  3. 11.3.Scikit-learn Implementation

  1. 12.1.Logistic Regression, KNN, Decision Tree, Random Forest

  2. 12.2.Confusion Matrix, Accuracy, Precision, Recall, F1

  3. 12.3.ROC and AUC

  1. 13.1.K-Means Clustering, Hierarchical Clustering

  2. 13.2.Dimensionality Reduction: PCA

  3. 13.3.Elbow Method and Silhouette Score

  1. 14.1.Train/Test Split and Cross Validation

  2. 14.2.Overfitting vs Underfitting

  3. 14.3.Hyperparameter Tuning (Grid Search, Random Search)

  1. 15.1.Importing and Cleaning Datasets

  2. 15.2.Applying EDA and Preprocessing

  3. 15.3.Model Selection and Evaluation

  1. 16.1.Text Cleaning: Tokenization, Lemmatization, Stopwords

  2. 16.2.Bag of Words and TF-IDF

  3. 16.3.Sentiment Analysis and WordCloud

  1. 17.1.Time Series Components

  2. 17.2.Plotting and Decomposing

  3. 17.3.Moving Average and Exponential Smoothing

  4. 17.4.Introduction to ARIMA

  1. 18.1.What is Deep Learning?

  2. 18.2.Introduction to Neural Networks

  3. 18.3.Keras Sequential API

  4. 18.4.Building and Evaluating Basic Models

  1. 19.1.Choose a Dataset

  2. 19.2.Define the Problem Statement

  3. 19.3.Data Cleaning, EDA, Model Building

  4. 19.4.Final Report and Presentation

  1. 20.1.Advanced Dataset Integration

  2. 20.2.Deploying ML Model with Streamlit or Flask

  3. 20.3.End-to-End Solution Presentation

Benefits

Our Dashboard offers 1500+ coding problems to sharpen skills and prepare for company-specific interviews. Track progress, build your profile, and boost job-readiness for successful technical interviews

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Our product provides real-time debugging assistance, allowing learners to efficiently identify and fix errors, enhancing their programming skills and understanding

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Our integrated IDE compiler offers a unified platform for writing, executing, and debugging code efficiently. With real-time execution and instant feedback, users can test and optimize their code seamlessly.

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we organize coding contests within the platform, offering users the opportunity to compete against peers, test their problem-solving abilities, and enhance their skills through time-bound challenges and real-world scenarios

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We maintain a personalized profile for each user, tracking their learning progress, performance in coding problems, and achievements,It also includes a record of completed contests, certifications earned, and coding skills developed etc

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This is one For You

Hands on training

Looking to enhance your Coding skills

Innovation Ideas

lets you create innovative solutions, explore technologies

Newbie Programmer

Budding Programmer , Wants to learn some tricks and tips

Upskilling your skills

A professional wanting to Update their skills

Gain a Competitive Edge With Our Professional Certificates

Master the latest programming languages and enhance your skill set with a recognized certificate.

unlock new career opportunities with a programming certificate

FAQ

Our program is one of the best data science courses because it blends strong fundamentals with real-time project experience, guided by mentors from the industry.
Yes, You will receive a recognized certificate, making it a data scientist certification course that can enhance your resume and job prospects.
Yes, this is a flexible data science online course designed for remote learning. You can access lectures, labs, and mentor support from anywhere.
This certified data science course is suitable for students, IT professionals, analysts, and engineers who want to pivot into data-driven roles or accelerate their careers.
Absolutely, We align with industry standards and help you prepare for globally acknowledged certifications for data science.