Master Data Science with eCareerpluz
Unlock your potential in the world of Data Science, one of the most in-demand skills in today's technology-driven world. At eCareerpluz, we offer a comprehensive, hands-on Data Science course that prepares you for a rewarding career in this dynamic field.
Master Data Science Overview
Ecareerpluz is your gateway to mastering Data Science, offering top-notch training in Madurai. Our program is designed to equip you with cutting-edge skills and industry-relevant expertise to excel in the ever-growing field of Data Science. +91 98433 09040
Why Choose eCareerpluz for Data Science?
Expert Instructors
Learn from industry professionals with years of experience in Data Science and Analytics.
Practical Training
Gain hands-on experience with real-world datasets and case studies.
Comprehensive Curriculum
Covers all aspects of Data Science, from basics to advanced topics like Machine Learning and AI.
Flexible Learning
Online and offline classes designed to suit your schedule.
Hands-on learning
Get hands-on experience through interactive labs, real-world scenarios, and projects that simulate workplace tasks.
Job Assistance
Resume building, mock interviews, and placement support to help you land your dream job.
Who Can Join?
1. Fresh Graduates
Start your career in Data Science with industry-relevant skills.
2. IT Professionals
Upskill to transition into high-demand Data Science roles.
3. Business Professionals
Use data to make better decisions and drive success.
4. Entrepreneurs
Leverage data science to grow and optimize your business.
5. Career Changers
Switch to a rewarding career in Data Science with no prior experience needed
6. Students
Gain an edge in placements by learning in-demand skills before graduation
No prior experience required! Basic math and interest in technology are all you need to begin
Upcoming Master Data Science Training Batches
Seeking a Date to Join the Course?
Master Data Science Course in Madurai Curriculum
The Master Data Science curriculum at e-Careerpluz is meticulously crafted to equip students with the essential skills and knowledge needed for a successful career in data science. Our course covers a comprehensive range of topics, ensuring that learners gain a deep understanding of data analysis, machine learning, and statistical modeling. Below is an overview of the course curriculum:
- What is Data Science?
- Applications of Data Science (e.g., healthcare, finance, retail)
- Data Science Use Cases
- Overview of Data Science Process: CRISP-DM methodology
- Tools & Technologies: Python, R, SQL, Excel, Tableau, etc.
- Python Basics:
- Data Types, Variables, and Operators
- Conditional Statements and Loops
- Functions, Modules, and Libraries
- File Handling (CSV, JSON)
- Python for Data Science:
- Libraries:
- NumPy: Arrays, Indexing, Broadcasting
- Pandas: DataFrames, Data Manipulation, Missing Values
- Matplotlib & Seaborn: Data Visualization
- Jupyter Notebooks and IDEs
- Libraries:
- Importing Data
- Handling Missing Data
- Encoding Categorical Variables
- Scaling and Normalization
- Outlier Detection and Treatment
- Exploratory Data Analysis (EDA):
- Univariate, Bivariate, and Multivariate Analysis
- Visualizing Trends and Relationships
- Linear Algebra: Matrices, Vectors, Dot Product
- Calculus: Derivatives and Optimization in Machine Learning
- Probability: Basics, Bayes’ Theorem, Probability Distributions
- Statistics:
- Descriptive Statistics (Mean, Median, Mode, Variance, Standard Deviation)
- Inferential Statistics (Hypothesis Testing, p-values)
- Regression Analysis and Correlation
- Optimization Techniques: Gradient Descent
- Supervised Learning:
- Regression: Linear, Logistic
- Classification: Decision Trees, Random Forest, SVM, KNN
- Unsupervised Learning:
- Clustering: K-means, Hierarchical Clustering
- Dimensionality Reduction: PCA, t-SNE
- Introduction to Ensemble Methods: Bagging, Boosting (e.g., XGBoost)
- Data Storytelling Principles
- Visualization Tools:
- Python Libraries: Matplotlib, Seaborn, Plotly
- Tableau, Power BI
- Dashboards and Interactive Visuals
- Best Practices for Presenting Data Insights
- Deep Learning:
- Basics of Neural Networks
- Introduction to TensorFlow/PyTorch
- CNNs for Image Processing
- RNNs for Sequential Data
- Natural Language Processing (NLP):
- Text Preprocessing (Tokenization, Lemmatization)
- Sentiment Analysis
- Introduction to Transformers (e.g., BERT)
- Overview of Big Data Tools: Hadoop, Spark
- Basics of Cloud Platforms: AWS, Google Cloud, Azure
- Distributed Data Processing
- SQL Basics: SELECT, INSERT, UPDATE, DELETE
- Joins, Subqueries, Indexes
- Database Design Concepts
- Working with Relational Databases (MySQL, PostgreSQL)
- Hands-on Projects on:
- Predictive Analytics (Sales Forecasting, Customer Churn)
- Classification Problems (Spam Detection, Fraud Detection)
- Clustering (Market Segmentation)
- Real-time Data Analysis
- Building a Complete Data Science Pipeline: Preprocessing to Deployment
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- Python, R, SQL
- Pandas, NumPy
- Matplotlib, Seaborn, Tableau
- TensorFlow, Keras (Basics)
With the skills you gain in our comprehensive Data Science program, you’ll be ready to excel in various high-demand roles across industries. Here's an overview of the exciting career paths you can pursue:
- Data Analyst
- Machine Learning Engineer
- Data Scientist
- Business Analyst
- AI Specialist
- Customer Segmentations
- Fake News Detection
- Speech Recognition through the Emotions
