What you'll get
- 38+ Hours
- 9 Courses
- Mock Tests
- Course Completion Certificates
- Self-paced Courses
- Technical Support
- Case Studies
Synopsis
- Develop practical expertise in Pandas and NumPy for efficient data handling.
- Strengthen Python programming skills tailored for data science applications.
- Gain foundational knowledge of statistics for analytics and machine learning.
- Learn to design and implement basic machine learning models.
- Understand neural network fundamentals using TensorFlow.
- Create meaningful data visualizations with Matplotlib and Seaborn.
- Perform end-to-end data analysis through hands-on projects.
- Utilize Anaconda and integrate data workflows with Azure Data Lake.
Content
| Courses | No. of Hours | Certificates | Details |
|---|---|---|---|
| Pandas with Python Tutorial | 5h 42m | ✔ | View Curriculum |
| Numpy and Pandas | 5h 9m | ✔ | View Curriculum |
| Pandas Project | 3h 14m | ✔ | View Curriculum |
| Courses | No. of Hours | Certificates | Details |
|---|---|---|---|
| Machine Learning with Tensorflow for Beginners | 13h 39m | ✔ | View Curriculum |
| Statistics for Data Science using Python | 3h 23m | ✔ | View Curriculum |
| Courses | No. of Hours | Certificates | Details |
|---|---|---|---|
| Applied Data Analytics Using Python | 5h 7m | ✔ | View Curriculum |
| Data Science with Python Project-Predict Diabetes on Diagnostic Measures | 1h 02m | ✔ | View Curriculum |
| Logistic Regression-Predicting the Survival of Passenger in Titanic | 2h 6m | ✔ | View Curriculum |
| Analyzing the Quality of White Wines Using NumPy | 1h 22m | ✔ | View Curriculum |
| Courses | No. of Hours | Certificates | Details |
|---|---|---|---|
| No courses found in this category. | |||
Description
This professional training program provides an in-depth introduction to data analysis and scientific computing using Python. It focuses on developing practical skills in handling structured and unstructured data using Pandas and NumPy. Rather than limiting learning to theoretical knowledge, the course emphasizes experiential learning through projects, exercises, and real-world scenarios.
The program also introduces complementary tools and technologies widely used in the data industry. Learners explore data visualization, basic machine learning techniques, and cloud-based data workflows, making the training highly relevant to current industry requirements. By the end of the course, participants develop the technical competence needed to pursue careers in data analytics, data science, and artificial intelligence.
Sample Certificate
Goals
- To build a solid understanding of Python-based data analysis tools.
- To enable learners to process, analyze, and visualize complex datasets.
- To introduce essential machine learning and statistical concepts.
- To prepare participants for data-driven professional roles.
- To develop practical, industry-relevant technical skills.
Objectives
By completing this course, participants will be able to:
- Use Pandas and NumPy effectively for real-world data tasks.
- Analyze datasets using structured and efficient techniques.
- Apply statistical methods to support data-driven decision making.
- Build and evaluate basic machine learning models.
- Create professional-quality data visualizations.
- Work with modern data platforms and cloud-based tools.
- Handle practical data science projects with confidence.
Highlights
- Project-based learning approach.
- Comprehensive coverage of Pandas and NumPy.
- Introduction to machine learning and neural networks.
- Practical exposure to data visualization techniques.
- Hands-on exercises using real datasets.
- Integration with Azure Data Lake and modern workflows.
- Step-by-step guidance from foundational to advanced concepts.
Requirements
- Basic knowledge of Python programming.
- Understanding of elementary mathematics and statistics.
- Access to a computer with Python or Anaconda installed.
- Interest in learning data analytics and machine learning.
Target Audience
- Students planning to begin a career in data science or analytics.
- Python programmers aiming to strengthen their data analysis skills.
- Data and business analysts work with large volumes of data.
- Individuals interested in ML & AI.
- Professionals involved in reporting, visualization, or data processing.
- Anyone seeking to master practical tools for data manipulation.
FAQ
Q1. Is prior programming experience required?
Learners should have a basic understanding of Python, but they do not need advanced programming knowledge.
Q2. Will the course cover machine learning?
Yes, the program introduces fundamental machine learning concepts and simple model building.
Q3. Do participants need to install any software?
Learners should have Python or Anaconda installed before starting the course.
Q4. Is this course suitable for beginners?
Absolutely. The content is structured to support both beginners and professionals.
Q5. Are real-world projects included?
Yes, the course includes practical assignments and projects based on real datasets.
Career Benefits
- Opens opportunities in data science, analytics, and AI roles.
- Builds highly demanded technical skills in Python, Pandas, and NumPy.
- Strengthens analytical thinking and problem-solving abilities.
- Enhances employability in technology-driven industries.
- Prepares learners for advanced paths in machine learning and data engineering.
- Provides hands-on experience valued by employers worldwide.
