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Advanced Data Science Certification with 100% Placement

πŸ’Ό 100% Pay after Placement | πŸ’° Classroom Training only | 🌍 Most updated course

Course Fee: Pay after placement only -Rs 56K+GST 18%. Limited seats only. Admission on personal interview. Only graduates BSC/BCA/BTech minimum 65%.

πŸ’Ό 100% Job Placement

Guaranteed placement with top companies after certification completion.

πŸ–₯️ Live Classes & Real-World Labs

Participate in live, instructor-led sessions and hands-on labs for practical skills.

🌍 Globally Recognized Certification

Earn a Data Science certification to unlock global career opportunities.

πŸ§‘β€πŸ« World-Class Trainers

Learn from experts with extensive industry experience in data science.

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6-Month Data Science Career Path

From Data Fundamentals to Advanced Machine Learning, build your data science career with Networkers Home’s comprehensive course.

Month 1: Data Foundations

Develop foundational skills in Python, data wrangling, and SQL for data science applications.

  • Python for Data Science
    • Understanding data types, variables, and control structures.
    • Functions, modules, and basic Python data science libraries (Pandas, NumPy).
  • Data Wrangling & Cleaning
    • Data importing, handling missing data, transformations, and merging techniques.
  • Introduction to SQL
    • SQL queries (SELECT, JOIN, GROUP BY), database management, and analysis.
Activities:

Lab: Data Cleaning | Project: Data Wrangling Challenge using SQL and Python

Month 2: Exploratory Data Analysis (EDA)

Explore data with visualizations and basic statistics to uncover insights.

  • Data Visualization with Python
    • Using Matplotlib and Seaborn for basic and advanced visualizations.
    • Crafting visuals that tell a compelling data story.
  • Statistical Analysis
    • Descriptive statistics, probability, and inferential statistics basics.
  • Hypothesis Testing
    • Significance tests, confidence intervals, and real-world applications.
Activities:

Lab: EDA on a Public Dataset | Project: Visual Data Storytelling

Month 3: Machine Learning Basics

Learn machine learning fundamentals, including supervised and unsupervised learning.

  • Supervised Learning
    • Key algorithms: Linear regression, decision trees, and support vector machines.
  • Unsupervised Learning
    • Clustering and association algorithms, including K-means and Apriori.
  • Model Evaluation
    • Metrics like accuracy, precision, recall, F1-score, and ROC curves.
Activities:

Lab: Building ML Models | Project: Classification on Real-World Data

Month 4: Advanced Machine Learning

Master advanced machine learning techniques, feature engineering, and model tuning.

  • Feature Engineering
    • Techniques to select, create, and transform features for model improvement.
  • Hyperparameter Tuning
    • Grid search, random search, and using libraries like Scikit-Learn.
  • Model Optimization
    • Improving model performance through advanced techniques like regularization.
Activities:

Lab: Model Tuning | Project: Predictive Modeling

Month 5: Deep Learning Fundamentals

Learn deep learning basics, neural networks, and model building with popular frameworks.

  • Neural Networks
    • Understanding layers, activation functions, and backpropagation.
  • Convolutional Neural Networks (CNNs)
    • Implementing CNNs for image classification and recognition.
  • Introduction to TensorFlow and Keras
    • Setting up deep learning models with TensorFlow/Keras.
Activities:

Lab: Image Classification | Project: CNN-based Model

Month 6: Real-World Applications & Capstone Project

Apply your skills in a capstone project, learning to deploy models and manage project lifecycles.

  • Data Science Project Lifecycle
    • From data collection to model deployment, understand end-to-end project handling.
  • Deployment and Monitoring
    • Deploy models on cloud platforms and monitor their performance.
  • Capstone Project
    • Complete a comprehensive data science project with real-world datasets.
Activities:

Project: End-to-End Data Science Solution

Apply for Data Science Course

The Trusted Placement Factory: Launching 41,000+ Careers

See how Networkers Home turns ambition into success with 41,000+ placements across India. Your career transformation starts here.

Start Your Success Journey

Get Hired by the Best πŸš€

Our students have successfully landed roles in top companies worldwide. Join the ranks of successful graduates with Networkers Home's placement support!

Frequently Asked Questions

Here are some common questions about our Pay-After-Placement Data Science course. Click on each to expand for details.

Career Path and Job Roles

Explore the lucrative career paths and job roles you can aim for after completing our Data Science course.

*Average salaries are displayed in lakhs INR per annum and may vary based on experience and location.

Project Work and Hands-On Labs

Our Data Science course includes extensive hands-on labs and real-world projects designed to build practical skills and a job-ready portfolio.

Project: Data Cleaning and Preprocessing

Learn data cleaning techniques by working on real-world messy datasets, handling missing values, outliers, and inconsistent formats.

  • Dataset: Public health data
  • Skills: Python, Pandas, data wrangling

Lab: Exploratory Data Analysis (EDA)

Conduct EDA on a public dataset to uncover patterns and insights using data visualization and descriptive statistics.

  • Dataset: Sales and revenue data
  • Skills: Matplotlib, Seaborn, data visualization

Project: Predictive Modeling

Build and evaluate predictive models to forecast future trends using supervised learning techniques.

  • Dataset: Financial forecasting data
  • Skills: Linear regression, decision trees

Lab: Machine Learning Pipeline

Implement an end-to-end ML pipeline from data ingestion to model evaluation, focusing on automation and scalability.

  • Framework: Scikit-Learn
  • Skills: Pipeline creation, cross-validation

Project: Deep Learning for Image Classification

Create a convolutional neural network (CNN) to classify images and improve accuracy with data augmentation techniques.

  • Dataset: Image dataset
  • Skills: CNN, TensorFlow, image processing

Capstone Project: Real-World Data Science Application

Work on a comprehensive project that covers the entire data science pipeline, from data cleaning to deployment, and present your findings.

  • Dataset: To be chosen based on student interest
  • Skills: End-to-end data science, storytelling
Build Your Portfolio with Us

Join Our Free Demo Class

Get a firsthand experience of our Data Science course. Join our expert-led session to explore the curriculum, teaching style, and career support we offer.

Live Interaction

Experience a live class with our instructors and get your questions answered in real time.

Explore the Curriculum

Preview the course syllabus and get insights into key topics and projects covered.

Career Guidance

Understand how our program prepares you for high-demand data science roles.

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Sample Resume after NETWORKERS HOME Course Completion

John Doe

Certified Data Science Specialist

πŸ“ Bangalore, India πŸ“ž +91-12345-67890 πŸ“§ [email protected]
linkedin.com/in/johndoe

Profile Summary

Data-driven Data Science professional with a certification from Networkers Home, skilled in data analysis, machine learning, and statistical modeling. Proven ability to transform complex datasets into actionable insights to support business decisions.

Education

Networkers Home

Certificate in Data Science (Completion Date: MM/YYYY)

Comprehensive training covering Python, Machine Learning, Data Visualization, and SQL.

Bachelor of Science in Computer Science

XYZ University, Bangalore

Graduated with Distinction (Year)

Professional Experience

Data Analyst Intern

ABC Company | Bangalore | MM/YYYY - MM/YYYY

  • Analyzed large datasets to identify trends and patterns, resulting in a 20% improvement in decision-making efficiency.
  • Created data visualizations using Python and Tableau to communicate insights to non-technical stakeholders.
  • Automated data collection and cleaning processes, reducing project time by 15%.

Freelance Data Scientist

Freelance | Remote | MM/YYYY - MM/YYYY

  • Built predictive models using machine learning algorithms to support client projects in retail and finance sectors.
  • Developed and deployed data processing pipelines, improving data accuracy by 25%.

Skills

Python Machine Learning Data Visualization SQL Statistical Analysis Data Cleaning Pandas TensorFlow

Practical Workshops Attended

  • Python for Data Science Workshop: Fundamentals of Python, data structures, and libraries for data science.
  • Data Wrangling & Cleaning Workshop: Techniques for handling missing data, transformations, and data preprocessing.
  • Exploratory Data Analysis Workshop: Data visualization and basic statistical techniques to uncover insights.
  • Machine Learning Basics Workshop: Introduction to supervised and unsupervised learning algorithms.
  • Advanced Machine Learning Workshop: Hyperparameter tuning, model optimization, and deployment.
  • Deep Learning Workshop: Neural networks, CNNs, and practical applications using TensorFlow and Keras.
  • Capstone Project Workshop: Developed an end-to-end data science solution with a real-world dataset.

Certifications

  • Data Science Certification - Networkers Home
  • Python for Data Science - Coursera
  • Machine Learning - Stanford University (Coursera)

References

Available upon request

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