Data Science And Analytics Training Course
- Home
- >
- Professional Training
- >
- Data Science And Analytics Training Course
| Course Level: | Beginner to Advanced |
| Course Duration: | 4 Months | 8 Months |
| Training Days: | Monday to Friday |
| Training Time: | 4 Hours/Day | Regular Office Hours |
| Course Mode: | In-class (Offline) at our premises |
| Course Type: | Job-Oriented Training |
| Course Start: | Upon Registration / Admission |
| Class Size: | 1-to-1 | No Groups | No Batches |
COURSE BENEFITS
-
Your Final Training Destination: We focus on real knowledge and practical skills—your training ends only when you secure a job.
-
Discover Your Strengths: We help you choose (or suggest) the right technology based on your abilities and career goals.
-
Recognize Your Skills: The entire program follows industry practices, and on successful placement, you receive an experience letter to validate your expertise.
-
Be a High-Paid Fresher: Our unique training and placement model helps you secure the best possible starting salary. If you receive a better offer than ours, you are free to join them.
-
No Limits on Learning: There is no fixed syllabus. Learn as much as you want—beyond standard topics—to build strong logical and technical skills.
What is Data Science?
Importance of Data Science in Today’s World.
Applications of Data Science in Various Industries.
Data Science vs Data Analytics vs Machine Learning vs AI.
Career Opportunities in Data Science.
This beginner-friendly data science course is designed to help any graduate freshers build a strong foundation in data analysis, machine learning, and data visualization.
Introduction to Python and Jupyter Notebook.
Python Basics (Variables, Data Types, Operators).
Control Flow (Loops, Conditional Statements).
Functions and Modules.
Working with Python Libraries
NumPy for Numerical Computing
Pandas for Data Manipulation
Matplotlib & Seaborn for Data Visualization.
Types of Data: Structured vs Unstructured.
Importing and Exporting Data (CSV, Excel, JSON).
Data Cleaning and Handling Missing Values.
Data Transformation and Feature Engineering.
Handling Outliers and Data Normalization.
Importance of EDA in Data Science.
Univariate and Bivariate Analysis.
Data Visualization Techniques.
Correlation and Covariance Analysis.
Detecting and Handling Outliers.
Descriptive Statistics (Mean, Median, Mode, Variance, Standard Deviation).
Probability Distributions (Normal, Binomial, Poisson).
Hypothesis Testing & Confidence Intervals.
Correlation vs Causation.
What is Machine Learning?
Types of Machine Learning (Supervised, Unsupervised, Reinforcement Learning).
Introduction to Regression and Classification.
Introduction to Clustering Algorithms.
Hands-on Implementation Using Scikit-Learn.
Understanding Business Problems through Data.
End-to-End Data Science Project Workflow.
Data Collection and Cleaning Best Practices.
Model Building and Evaluation.
Introduction to Databases and SQL.
Writing SQL Queries (SELECT, JOIN, GROUP BY, WHERE, HAVING).
Data Aggregation and Filtering.
Using SQL for Data Analysis.
Advanced Matplotlib & Seaborn for Visualization.
Building Interactive Dashboards with Power BI/Tableau (optional).
Storytelling with Data.
This structured course will equip for any graduate with the necessary skills to start a career in data science. this Course is customize based on your requirement.
Fresh Graduates: Individuals who have recently completed their education and are looking to enter the field of software development or DS.
Junior Developers/Admin: Developers with limited experience who want to enhance their skills with containerization technologies.
Career Switchers: Professionals from different fields who are transitioning into tech and want to understand the basics of Docker.
Students: Current students in computer science or related fields who wish to gain practical skills in Docker.
LEARN WHAT SUITS YOU BEST
No limits on learning, duration, interviews, or salary growth. Learn as much as you want and get fully prepared for your first job—with complete freedom to grow at your pace.
4 MONTHS TRAINING(CODE :- PTP 4)
-
4-month intensive training program
-
Monday to Friday (4 hours per day)
-
Only practical, hands-on learning
-
Individual 1-to-1 personalized training
-
Training by professional industry developers
-
Stipend offered based on performance
-
Guaranteed job through our on-job training model
-
Ideal for Diploma/Graduates (any stream), career switchers, and IT enthusiasts
12 MONTHS TRAINING(CODE :- PTP 12)
-
Up to 12 Months or Until Placement
-
Monday to Friday (full day Adjusted Based on Work Opportunity)
-
Live Work-Based Training with a Collaborative Team
-
1 to 1, Real-World Project Experience & Industry-Standard Skills
-
Unlimited Placement Support with Dual Job Opportunities
-
Industry Diploma Recognized as Experience + Training Certificate
-
Join as a Fresher, Graduate as an Experienced Professional Developer
-
10+2, Diploma/Graduate (Any Stream), Career Changers & IT Enthusiasts.
GLOBAL ACCREDITATIONS
Contact Us
Trending Courses
Popular Posts
-
September 20, 2019 Top 10 IT Training Courses For fresher india -
-
September 20, 2019 10 Software Course You can learn in 6 Weeks or less