Data Science

OVERVIEW OF DATA SCIENCE

Data science is a multidisciplinary field that combines various techniques and
processes to extract insights and knowledge from structured and unstructured
data. It integrates methods from statistics, computer science, and domain-specific
knowledge to analyze and interpret complex data.

CORE COMPONENTS OF DATA SCIENCE

1. Data Collection: Gathering raw data from various sources, such as databases,
   APIs, web scraping, sensors, and surveys.
2. Data Cleaning: Preparing data for analysis by handling missing values, outliers,
   and inconsistencies.
3. Data Exploration: Understanding data through descriptive statistics,
   visualizations, and exploratory data analysis (EDA) to identify patterns and
   relationships.
4. Data Modeling: Applying statistical and machine learning techniques to build
   predictive or descriptive models that help answer specific questions or solve
   problems.
5. Data Interpretation: Analyzing model results to draw meaningful conclusions
   and making data-driven decisions.

Data Visualization: Creating charts, graphs, and dashboards to effectively
communicate findings and insights to stakeholders.

COMMON TOOLS IN DATA SCIENCE

1. Programming Languages: Python and R are the most widely used languages due
   to their rich libraries and ease of use. Other languages like SQL, Java, and Scala
   are also utilized.
2. Libraries and Frameworks: For Python, libraries such as NumPy, pandas, scikit-
   learn, TensorFlow, and PyTorch are common. R has packages like ggplot2, dplyr,
   and caret.
3. Data Visualization Tools: Tools like Tableau, Power BI, and matplotlib (Python)
   or ggplot2 (R) are used to create visual representations of data.
4. Big Data Platforms: Technologies like Apache Hadoop, Apache Spark, and
   cloud-based solutions (e.g., AWS, Azure, Google Cloud) are used for processing
   and analyzing large datasets.

DATA SCIENCE COURSE CONTENT

1. Introduction to Data Science
2. Programming for Data Science
3. Data Collection and Acquisition
4. Data Cleaning and Preparation
5. Exploratory Data Analysis (EDA)
6. Statistical Analysis
7. Machine Learning
8. Advanced Machine Learning Techniques
9. Big Data Technologies
10. Data Visualization and Communication

DATASCIENCE SALARY

1. Entry-Level Data Scientist

United States: $65,000 – $90,000 per year.

Europe: €40,000 – €60,000 per year.

Asia: $20,000 – $50,000 per year (varies significantly by country).

2. Mid-Level Data Scientist

United States: $90,000 – $130,000 per year.

Europe: €60,000 – €90,000 per year.

Asia: $40,000 – $80,000 per year.

3. Senior-Level Data Scientist

United States: $130,000 – $200,000+ per year.

Europe: €90,000 – €130,000 per year.

Asia: $80,000 – $150,000 per year.

JOB PROSPECT IN DATASCIENCE

Data Scientist

Business Intelligence (BI) Analyst

Data Engineering Intern

Data Engineer

Machine Learning Engineer

Quantitative Analyst (Quant)

Business Intelligence (BI) Developer

Senior Data Scientist

Lead Data Scientist

Data Science Manager