Data Science Classes NJ

In this comprehensive data science program, individuals will learn a variety of critical skills to become a data scientist. Students will learn to code with Python, create machine learning models, automate tasks like web scraping, and interact with databases using SQL. Topics include data analysis with Python's Numpy and Pandas packages, data visualization, predictive analytics, machine learning, SQL querying, Python automation, and web scraping. Students will learn hands-on by working in Python and SQL and will complete the program with the skills they need to enter the field of data science. This program offers flexible scheduling and provides a free retake for students to refresh the material.

This online data science program is meant to get students ready for a career in data science. The program covers the key components for data science, including SQL, Python, statistics, and machine learning. Students will start coding in Python using Jupyter notebooks, learn the statistics behind machine learning, apply machine learning techniques, and work on data science projects in this data science course. Students will also receive career coaching and job support during the program for help finding a job in data science. The online program offers flexible scheduling options, including full-time over 5 months, part-time over 10 months, and self-paced for up to 15 months.

This full-time, accredited data science bootcamp covers data wrangling and exploratory data analysis using Python's statistical and data visualization packages. It also teaches regression techniques, web scraping, classification techniques using supervised and unsupervised models, and natural language processing. Finally, the courses finishes off with a capstone data science project where students can showcase their knowledge and talent.

This course offers a rigorous introduction to data science in 24-weeks. Graduates will be prepared for careers as database administrators, data scientists, and data engineers. The curriculum covers Python, SQL, Excel, Tableau, and JavaScript, giving students a foundation in data science and visualizations. Students will also leave the program with a valuable professional portfolio, ready to show future employers.

This data science program is designed to help individuals with a math background and some familiarity with Python programming bolster their skills and get up to speed and launch their data career. Through their blended learning model, students will be able to hone their data skills through fundamental preparatory work, in-class project work, and though the support of a devoted career coach. Students in this course will start their data science journeys by learning fundamental concepts around Python programming and leveraging programming tools like GitHub. As the course progresses, students will explore additional programming concepts like NumPy, utilizing Unix commands, using Pandas to clean and extract data, and web scraping tools. The course also covers statistical modeling and regressions, machine learning models, NLP, and a few other advanced topics and trends that are helpful to data scientists of all levels.

This course on data wrangling with Python offers a 3-day comprehensive introduction. The purpose of this course is to give an immersive foundation that equips students with the most critical data analysis tools. Students will learn how to work with NumPy, Pandas, and MatPlotLib to calculate descriptive statistics, work with alternative data sources, and scrape web pages. The course culminates with a real-life data wrangling project.

This course teaches the fundamentals of SQL querying. This 1-day program teaches students how to execute a simple query, perform a conditional search, work with functions, and organize data. Further, students will learn how to retrieve data from multiple sources and export query results via a text or XML file.

This 1-day course builds on the fundamentals of SQL querying. This intermediate program teaches advanced querying techniques. The coursework will cover the use of subqueries to perform advanced querying, manipulating table data and table structure. Students will learn how to work with views, index data and manage transactions.

This 3-day introductory course teaches the basics of SQL databases. Through the use of labs and lectures, students will learn the fundamentals of data modeling, the use of relational databases, and the normalization of raw data. Students will also learn how to design relationships, evaluate query performance, and use stored procedures.

This 2-week summer course for high school and college students dives into Python programming and its applications in data science. After they master some Python fundamentals, students move onto more advanced topics. Using platforms like Matplotlib, Pandas, and scikit-learn, students learn how to input, graph, and analyze data. This course gives attendees a head start on the most popular and versatile programming language and the fundamentals for a career as a data scientist or analyst.

This 2-week advanced Python course helps high school or college students expand their Python programming skills to machine learning and automation. This course breathes life into industry buzzwords like automation and machine learning, so students can meaningfully contribute to large and small organizations. Once participants master tools like logistic and linear regression, students learn more advanced topics, including algorithms with k-nearest neighbor, decision tree, and random forest algorithms. As a result, students quickly master sought-after skills such as variance, bias, fitting, and other statistical concepts.