Data Science Expertise

Advance your career with our Data Science Expertise course, offering comprehensive training in data analysis, machine learning, and real-world projects to equip you with the skills needed for success.

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Total Courses

Level

Beginner

Duration

25 Days

Schedule

Flexible

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Key Features Of This Course

Comprehensive Curriculum: Covers key areas such as statistical analysis, machine learning, data visualization, and big data technologies.

Hands-on Experience: Utilizes popular data science tools and programming languages like Python and R for practical learning.

Real-World Projects: Includes projects and case studies to provide practical insights into industry applications.

Advanced Techniques: Teaches data cleaning, feature engineering, and predictive modeling for in-depth knowledge.

Balanced Focus: Emphasizes both theoretical understanding and practical skills.

Career Preparation: Equips individuals for a successful career in data science.

SKILLS COVERED

Statistical Analysis

Machine Learning

Data Cleaning

Data Mining

Deep Learning

Predictive Modeler

Course Details

Introduction – Data Science

1. Evolution of Data Science
2. Roles & Responsibilities of Data Scientist
3. Supervised & Unsupervised learning
4. Machine learning
5. Deep learning and Artificial Intelligence

Statistics Concepts

1. Probability
2. Bayesian Inference
3. Hypothesis testing
4. Descriptive Statistics
5. Statistical Distribution(Discrete and continuous)

Frameworks

1. Anaconda Framework
2. Jupiter notebook and Spyder IDE’s
3. Python Data types

Linear and Logistic Regression

1. Linear regression
2. Logistic regression
3. Difference between Regression and Classification
4. Building a model using Linear and Logistic Regression

Clustering (K-means & KNN)

1. What is clustering?
2. Difference between K-means and KNN
3. Different Use cases of clustering
4. Building a model using K-means and KNN

Data Science and Machine Learning

1. Data Wrangling
2. Time Series Analysis
3. Big Data Processing
4. Model Deployment

Data Science and Social Media Analytics

1. Descriptive and Inferential Statistics
2. Classification
3. Data Ethics and Privacy
4. Data Storytelling

Mastering Data Science

1. Data Science Tools
2. Domain Knowledge
3. Ensemble Methods
4. A/B Testing

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JOB ROLES

Data Scientist

Data Analyst

Machine Learning Engineer

Quantitative Analyst

Data Engineer

Frequently Asked Questions

Are there any prerequisites for enrolling in the Data Science Course?

Basic knowledge of programming and statistics is recommended. Familiarity with Python or R is also beneficial.

Is this course suitable for beginners?

Yes, the course is designed to cater to beginners as well as those with some experience in data science.

What is Data Science?

Data Science is a multidisciplinary field that uses scientific methods, processes, algorithms, and systems to extract knowledge and insights from structured and unstructured data.