Data science classes, bootcamps and certificates in NYC

In this Python course, you'll discover how to harness its power to extract data from websites efficiently. You'll learn to automate tasks and gather valuable data from the internet using HTML/CSS, Python basics, and web scraping. Whether you're interested in social media, e-commerce, or government affairs, the ability to collect up-to-date data from the web is a valuable skill. Through hands-on exercises, you'll master Python loops to process numerous pages effortlessly, allowing you to grab precisely the data you need and avoid common pitfalls. This course is perfect if you have a keen interest in coding or you want to utilize Python for web or software development pursuits.

Data can only be so useful if you can’t make it clear and obvious what conclusions you hope are drawn from it. Microsoft PowerBI is a versatile data visualization application that is perfect for anyone looking to transform their datasets into interactive charts, maps and graphs that can be used to address stakeholders, explain datasets and draw viewers attention to specific aspects of the data that you want them to see. This can help you make connections that aren’t otherwise apparent, persuade audiences or make your point more forcefully. Learning PowerBI (or other data visualization tools like Tableau) is vital for anyone hoping to work in a field that combines data science and communication.

Python for Finance Bootcamp offers advanced training in Python for finance professionals, covering key areas such as financial libraries, API usage, and risk modeling. With a focus on gathering and manipulating financial data, you’ll learn to fetch APIs for company and economic data and analyze SEC financial statements. The course delves into building risk models, including VAR models and Monte Carlo simulation, using Python libraries. Ideal for financial analysts, risk managers, and portfolio managers, as well as those aspiring to careers in finance technology and data analysis, this course equips you with skills for navigating the financial landscape.

This immersive programming course at Practical Programming introduces students to machine learning techniques that are used for solving real-world problems. Starting with linear and logistic regression, you'll progress to more advanced algorithms like k-nearest neighbors and decision trees. You'll also delve into statistical concepts such as bias, variance, and overfitting to ensure robust model accuracy. The course emphasizes practical skills and focuses on applying machine learning algorithms to real-world scenarios, supported by visual explanations of mathematical foundations. You should have prior knowledge of Python programming and familiarity with libraries like Numpy and Pandas.

You’ll learn how to harness the power of SQL to transform raw data into actionable insights in this SQL training program. Starting from the basics of navigating databases, you'll progress to writing SQL queries to extract specific information. Discover advanced techniques such as filtering, grouping, and combining data from multiple tables using join statements, aggregate functions, and subqueries. This hands-on course utilizes Microsoft SQL Server and SQL Server Management Studio (SSMS) to execute queries and explore databases. With SQL being essential for various roles including business analysts, data scientists, web developers, and more, mastering this skill opens doors to opportunities in data-driven industries.

In this comprehensive program at NYIM Training, you'll master Excel, SQL, and Tableau, the top tools in data analysis and visualization. Through real-world projects, you'll learn to organize, analyze, summarize, and visualize data so you can extract insights and take action. This bootcamp covers everything from beginner to advanced levels in Excel, SQL, and Tableau, making it suitable for learners of all backgrounds. In the Excel Bootcamp, you'll dive into data manipulation, chart creation, Pivot Tables, and automation. The Tableau Bootcamp focuses on data visualization and analysis, while the SQL Bootcamp teaches querying databases, joining tables, and advanced SQL functions.

This program at New Horizons caters to Python developers who want to master key libraries for data science tasks. The curriculum employs a user-friendly Jupyter Notebook format to cover NumPy for numerical data processing, Pandas for data analysis, and Matplotlib and Seaborn for visualization and statistical reporting. You’ll learn to use the data science tech stack required by top companies, blending practical case studies with the underlying mathematical theory behind data science algorithms. By mastering data science skills and building a portfolio of real-world projects, you’ll be prepared to analyze, visualize, and gain insights from data.

Discover the rising importance of R among business analysts, statisticians, and data scientists for statistical analysis and machine learning applications. Introduction to R Programming focuses on mastering the practical aspects of the R programming language, with numerous hands-on labs to reinforce theoretical knowledge. The curriculum covers a range of topics including functional programming, managing environments, data visualization, and extending R functionalities. Through lab exercises, participants will delve into essential tasks such as data import/export, statistical modeling, and efficient usage of R for various analytical tasks. Whether starting with the basics or exploring advanced techniques, this course equips you with the tools needed to harness the power of R for data science. This course is excellent for business analysts, technical managers, and programmers seeking to enhance their skills in statistical computing and data manipulation.

This course will equip you with essential functions, formulas, and advanced techniques such as Pivot Tables and VLOOKUP that you need to utilize Excel as a data analytics program. Whether you're new to Excel or want to delve deeper into data analytics, this class offers a comprehensive learning opportunity. Explore core functions, statistical tools, and data visualization methods while mastering sorting, filtering, and grouping data efficiently. Elevate your skills with tips, tricks, and basic macro creation tailored for effective data analytics work. You’ll dive into hands-on projects under the mentorship of experienced instructors to optimize your workflow and gain practical experience in efficient data analysis.

In the world of finance, Python offers powerful tools for analyzing historical data and predicting future outcomes with speed and accuracy. In this course at Practical Programming, you’ll start with advanced Python and statistical concepts, such as object-oriented programming and regression models, and then delve into building predictive models using real-world financial data. You’ll explore financial statements and ratios, learning to extract data and compute ratios using Python. Then, you’ll tackle topics like present value and cost of capital and apply these concepts to build predictive financial models. You’ll learn practical applications for developing budgeting models solely using Python, and you’ll learn to visualize and export your findings for decision-making. This course is ideal for professionals in finance, risk management, reporting, investments, and financial management.

This live online summer program is tailored for high school students looking to learn the essential principles of Python programming and its practical applications in data science and machine learning domains. By mastering Python, you'll swiftly transition to utilizing it for diverse data analysis projects. Python stands out as the go-to language for programmers due to its blend of robustness and user-friendliness, which also makes it an ideal starting point for beginners. The curriculum will give you a solid foundation in Python coding and then progress to data science tools like Pandas, Matplotlib, and Sci-Kit learn. These tools will enable you to manipulate, visualize, and interpret complex datasets, while also introducing you to fundamental machine learning algorithms. Geared towards high school and college students keen on honing their coding skills, this program promises a comprehensive learning experience in Python and data science essentials.

Enrolling in a data science class not only equips you with specialized technical skills but also opens doors to lucrative career opportunities. With the increasing demand for data scientists in various industries, mastering data science techniques can lead to well-paying job prospects. Moreover, data science skills are versatile and applicable across a wide array of fields, so you’ll have flexibility in your career path.

Beyond the technical aspects, data science classes help you develop soft skills that are crucial for professional success. Through hands-on projects and collaborative learning environments, you’ll enhance your critical thinking and problem-solving abilities. Effective communication and teamwork are also emphasized, as data science projects often require collaboration and sharing of insights. Additionally, the structured nature of data science courses promotes effective time management skills, preparing you to meet project deadlines and consistently deliver high-quality work.

New York is one of the top states for employment in data science, with over 14,000 jobs across the state paying an average salary of $128,200. Data science careers in NYC are thriving, with opportunities spanning across various industries such as finance, healthcare, e-commerce, and media. NYC’s economy has been driven in large part by the securities industry, and Wall Street, for the past half-century. The finance sector, which includes Wall Street and major banking institutions, is a hotbed for data science professionals. Companies in this sector rely on data analysts and data scientists to analyze market trends, develop predictive models, and optimize investment strategies. 

Rapid growth in the $189 billion NYC tech sector over the last decade has propelled NYC into the world’s second-largest technology hub. NYC’s $10M public-private investment in the NYC Tech Talent Pipeline has created workforce programs that have engaged over 400 employers and 17 local colleges. NYC's tech industry is actually a cluster of thriving industries. This vibrant tech ecosystem fosters innovation and collaboration, making it an ideal environment for data science professionals to excel and advance their careers. With its diverse range of industries and competitive salaries, NYC offers abundant opportunities for those with coding and data science skills to thrive and make a significant impact in their field.

When you’re looking for the right data science course for you, it may seem difficult to distinguish between the various options. You may be concerned about how it will help you advance your career, whether you’ll have the skills to master data science, or whether it will fit into your busy schedule. First, take a look at the course content to ensure it covers the topics you want to learn, such as programming languages (e.g., Python, R), machine learning algorithms, data visualization, and statistical analysis. Seek courses that provide practical experience through projects or case studies, as this will help reinforce your understanding and skills and you’ll have a portfolio to share with employers. 

Look for instructors who are experienced professionals in the data science industry. Their expertise will enhance your learning and provide valuable insights into industry practices and trends. Additionally, consider programs that offer networking and collaboration with other students who can offer a supportive community and valuable collaboration. Assess whether the program's format fits your learning preferences and schedule. Some courses offer live classes with interactive sessions, while others provide recorded lectures and self-paced modules. Choose a format that aligns with your lifestyle and allows flexibility for your schedule. Lastly, inquire about any career placement assistance offered by the program. Having support in finding job opportunities can be instrumental in launching your career in the data science field.