Arash Naseri

The resume belongs to an individual who is seeking an entry-level job in data science. The candidate has a Ph.D. in mechanical engineering and has obtained certification in Associate Data Science and Associate Data Analysis from DataCamp. The resume lists the candidate's education, certifications, skills, and work experience in research and data analysis. The candidate possesses programming skills in Python and R and has experience with data analysis, data visualization, and machine learning algorithms. He also has experience in database management and has collaborated with interdisciplinary teams to design and implement solutions. The resume concludes with references available upon request.

Data Scientist Associate

• As part of the Omdena Nairobi Chapter Urban Growth project, I collaborated with a team of data scientists and urban planners to develop machine-learning solutions for urban planning and management challenges in African cities. This experience provided me with hands-on knowledge of various machine learning algorithms and techniques, as well as skills in data collection, cleaning, and analysis. Additionally, I gained valuable experience in presenting data-driven insights to decision-makers.
• Completed a Python Fundamentals track, consisting of 4 courses, 1 skill assessment, and a total of 15 hours of learning, gaining foundational skills in Python programming, including data cleaning and manipulation, data visualization using Matplotlib, and working with DataFrames and dictionaries using pandas.
• Completed a Machine Learning Fundamentals with Python track, consisting of 4 courses, 1 skill assessment, and a total of 16 hours of learning, gaining an understanding of supervised and unsupervised learning, linear classifiers, and neural networks using Keras.
• Completed a 90-hour Data Scientist with Python certification program track, including 23 courses, 6 projects, and 3 skill assessments, demonstrating expertise in data manipulation, visualization, and machine learning techniques using popular Python libraries.
• Completed a 36-hour Data Analyst with Python track, consisting of 9 courses and 2 skill assessments, gaining expertise in data manipulation, exploratory data analysis, and statistics skills.
• Completed a 12-hour Image Processing with Python track, consisting of 3 courses, gaining expertise in image processing and analysis, including image pre-processing, enhancement, restoration, and building powerful deep learning image classifiers using convolutional neural networks.