Data Scientist Bootcamp - In collaboration with IBM

Data Scientist Bootcamp - In collaboration with IBM

A unique learning and certification program!

About the Bootcamp

This data science bootcamp, in partnership with IBM, accelerates your career in data science and provides you with the world-class education and skills needed to succeed in this field. The course offers comprehensive training in the most in-demand skills in data science and machine learning, with hands-on exposure to key tools and techniques, including Python, R, Tableau, and machine learning concepts. Become a data scientist by diving into the nuances of data interpretation, mastering techniques such as machine learning and powerful programming skills to take your data science career to the next level.

This collaboration between AVC and IBM introduces participants to an integrated blended learning approach that makes them experts in data science. This data science course, in collaboration with IBM, will help students prepare for leading positions as data scientists.

Key Features

• Course and material in English
• Beginner - Advanced level for aspiring professional
• 11 months long live online bootcamp and eLearning (self-paced)
• Class is held mostly every weekend
• 1 year access to self-paced eLearning content & class recordings
• 38 hours eLearning video content
• 240 hours study time recommendation
• Exclusive Hackathons and Ask-Me-Anything sessions by IBM
• Top-notch curriculum with integrated labs
• Obtain industry-recognized IBM certificates for IBM courses
• Live online Masterclasses delivered by IBM experts.
• Certification for each courses and Bootcamp certification upon completion

Outcomes of the Program

• Acquire an in-depth understanding of data structure and data manipulation.
• Understand and use linear and non-linear regression models and classification techniques for data analysis.
• Acquire an in-depth understanding of supervised and unsupervised learning models such as linear regression, logistic regression, clustering, dimensionality reduction, K-NN and pipelines.
• Perform scientific and technical calculations using the SciPy package and its sub-packages, for example: Integrate, Optimize, Statistics, IO and Weave.
• Gain experience in mathematical calculations using the NumPy and scikit-learn packages.
• Master the concepts of recommendation engines and time series modeling and gain a working knowledge of the principles, algorithms and applications of machine learning.
• Learn how to analyze data with Tableau and become proficient in building interactive dashboards.

Data Science Certification Learning Path

1. Programming Essentials
2. SQL Certification Course
3. Python for Data Science (IBM)
4. Applied Data Science with Python
5. Machine Learning using Python
6. Tableau Desktop Specialist Certification Training
7. Data Scientist Capstone

Optional Courses - Bonus Material

• Business Analytics with Excel
• R Programming for Data Science
• PL-300 Microsoft Power BI Certification Training
• Essentials of Generative AI, Prompt Engineering & ChatGPT

Tools covered

• Python
• Scikit Learn
• Tableau
• PowerBI
• Numpy
• PyTorch
• Midjourney
• Pandas
• Seaborn
• SciPy
• MySQL
• ChatGPT
• DALL-E2
• Bard

Who Should Enroll in this Program?

The Data Science role requires an amalgam of experience, Data Science knowledge, and using the correct tools and technologies. It is a solid career choice for both new and experienced professionals. Aspiring professionals of any educational background with an analytical frame of mind are most suited to pursue the Data Scientist Bootcamp

• IT Professionals
• Analytics Managers
• Business Analysts
• Banking and Finance Professionals
• Marketing Managers
• Supply Chain Network Managers
• Beginners or Recent Graduates

Prerequisites

There are no formal education needed. However, professionals wishing to succeed in this data science training course should have the following:

• Basic knowledge of mathematics and statistics
• Basic understanding of any programming language

Learning Path

Course 1: Programming Essentials

Key learning objectives

• Acquire proficiency in both procedural and object-oriented programming
• Recognize the advantages and benefits of using Python as a programming language
• Learn about the various types of loops in Python
• Explore the concept of variable scope within functions
• Explain the principles and characteristics of object-oriented programming
• Become familiar with Jupyter Notebook and its practical applications
• Implement Python identifiers, indentations, and comments effectively
• Understand Python’s data types, operators, and string functions
• Describe methods, attributes, and access modifiers in Python

Course 2: SQL Certification Course

Key learning objectives

• Develop a comprehensive understanding of databases and their relationships
• Acquire expertise in various SQL lessons, including filtering, ordering, aliasing, aggregate commands, grouping, conditional statements
• Learn how to use common query tools and work with SQL commands
• Master transactions, table creation, and views for efficient database management
• Explore different SQL functions such as string, mathematical, date and time, and pattern-matching functions
• Comprehend and execute stored procedures to perform complex operations
• Understand user access control functions to ensure database security

Lesson 3: Python for Data Science (IBM)

Key learning objectives

• Create your first Python program using variables, strings, functions, loops, and conditions
• Understand and apply concepts related to lists, sets, dictionaries, conditions, branching, objects, and classes in Python
• Utilize the pandas library to load, manipulate, and save data, and read and write files in Python

Lesson 4: Applied Data Science with Python

Key learning objectives

• Explore the processes of data preparation, model building, and evaluation
• Apply Python concepts related to strings, Lambda functions, and lists comprehensively
• Develop a strong understanding of NumPy and its applications, including array indexing and slicing techniques
• Apply principles of linear algebra in data analysis, including its application in calculus
• Gain a clear understanding of statistical concepts like skewness, covariance, and correlation
• Calculate measures of central tendency and dispersion in data
• Describe the null hypothesis and alternative hypothesis in hypothesis testing Examine different
• Work with pandas’ two primary data structures: Series and DataFrame.
• Prepare, format, normalize, and standardize data using data binning techniques
• Create effective visualizations using Matplotlib, Seaborn, Plotly, and Bokeh

Course 5 - Machine Learning using Python

Key learning objectives

• Examine various types of machine learning and understand their unique characteristics
• Analyze the machine learning pipeline and gain a comprehensive understanding of key operations involved in machine learning operations (MLOps)
• Explore supervised learning and its wide range of applications
• Understand the concepts of overfitting and underfitting and learn techniques to detect and prevent them
• Analyze different regression models and identify their suitability for specific scenarios
• List various types of classification algorithms and comprehend their specific applications
• Master various types of unsupervised learning methods and determine their appropriate use
• Gain a deep understanding of different clustering techniques within unsupervised learning
• Examine different ensemble modeling techniques, such as bagging, boosting, and stacking
• Evaluate and compare different machine learning frameworks, including TensorFlow and Keras
• Build a recommendation engine using PyTorch

Course 6 - Tableau Desktop Specialist Certification Training

Key learning objectives

• Acquire expertise in various visualization techniques, such as heat maps, treemaps, waterfall charts, and Pareto charts
• Skillfully work with filters, parameters, and sets to manipulate data effectively
• Become proficient in utilizing special field types and Tableau-generated fields and creating and employing parameters
• Learn how to construct different charts, interactive dashboards, and captivating story interfaces and how to share insights effectively
• Gain proficiency in data blending, creating data extracts, and efficiently organizing and formatting data
• Understand the importance of metadata and its application in Tableau
• Master various calculations, including arithmetic, logical, table, and level of detail (LOD)

Course 7 - Data Scientist Capstone

Key learning objectives

• Data Processing: Utilizing various techniques to transform raw data into meaningful insights
• Model Building: Employing techniques such as regression and decision trees to create accurate and intelligent machine learning models capable of making predictions
• Python or SAS: Developing your model and conducting a complete model-building exercise, including data splitting, testing, and validating data using the k-fold cross-validation process
• Model Fine-tuning: Applying various techniques to enhance the model’s accuracy and selecting the bestperforming champion model
• Dashboarding and Result Presentation: Using Tableau to create a dashboard with meaningful insights to present your final results

Optional courses - Bonus material

1. Business Analytics with Excel

Enroll in this course to gain practical, data-driven decision-making skills by mastering data analysis and statistics. Leveraging Excel, you will acquire the expertise to perform sophisticated data analytics, empowering you to make informed business decisions confidently.

Key learning objectives

• Understand the importance of business analytics and its role in various industries
• Learn how to analyze complex data sets efficiently using pivot tables and slicers
• Grasp the fundamentals of Excel analytics functions and conditional formatting
• Solve stochastic and deterministic analytical problems using Excel’s powerful tools, including Scenario Manager, Solver, and Goal Seek
• Apply statistical tools and concepts like moving averages, hypothesis testing, ANOVA, and regression to data sets using Excel
• Effectively represent your findings using charts and dashboards
• Get introduced to the latest Microsoft analytics tools and technologies

2. R Programming for Data Science

R programming is a vital tool for data analysis and is essential for aspiring data science professionals. This course teaches you how to write R code, explore R’s data structures, and create custom functions. By the end of the course, you will be well-prepared to embark on your first data analysis project

Key learning objectives

• Learn about fundamental concepts such as math, variables, strings, vectors, factors, and vector operations in R
• Gain essential knowledge about arrays and matrices, lists, and data frames
• Explore conditions and loops, functions in R, objects, classes, and debugging
• Master the art of accurately reading and handling text, CSV, and Excel files
• Learn how to save and write data objects in R
• Understand and effectively work with strings and dates in R

3. Microsoft Power BI Certification Training

Microsoft Power BI offers robust tools to analyze data and extract valuable business insights through interactive dashboards. This comprehensive training course on Power BI empowers you to fully harness its potential, enabling you to solve business challenges and improve operations effectively. Throughout the course, you’ll learn to develop dashboards from published reports expertly, utilize Quick Insights to discover valuable patterns rapidly and adopt practical approaches for various tasks performed within Power BI, from data gathering to in-depth analysis. Additionally, the course provides helpful troubleshooting techniques to address various issues that may arise while using Power BI.

Key learning objectives

• Create dynamic dashboards from published reports, enhancing data visualization and interactivity
• Rapidly generate visuals and dashboards with quick insights to gain valuable insights from your data
• Utilize natural language in the Q&A feature to generate visuals for actionable insights
• Create and manage data alerts to stay informed of important changes in your data
• Learn best practices for report layout and data visualization to maximize the impact of your reports
• Incorporate shapes into your reports to design and emphasize key elements to create narratives
• Integrate custom visuals into your reports and dashboards
• Complete a comprehensive Power BI data analysis and visualization project from start to finish

4. Essentials of Generative AI, Prompt Engineering & ChatGPT

In this course, participants will comprehensively study generative AI models, particularly ChatGPT. The curriculum covers essential principles of Generative AI, prompt engineering, explainable AI,conversational AI, ChatGPT, and other large language models.

5. Industry Masterclass by IBM

Attend this online interactive industry master class to gain insights about Data Science advancements and AI techniques.

QUESTIONS AND ANSWERS

How long does it take to complete Bootcamp?

Thanks to the combination of e-learning and live online bootcamp, the program normally takes 11 months (5–10 hours/week).

However, you can complete it faster upon request. Don't hesitate to contact us for a better solution!

Some people can go through the program fairly quickly (about 3 months), while others need more time. Note: Some other master's programs take longer. This is an estimate.

You will have access to the program's e-learning videos and recorded lessons for 365 days.

What is a Bootcamp for Data Scientists?

Data science courses are educational programs designed to provide students with the skills and information necessary to use programming, statistics, machine learning, and domain expertise methods to analyze, evaluate, and extract valuable insights from large and complex data sets. In this data science course, you will learn about many concepts of varying complexity—from beginner to intermediate and advanced levels.

What is the value of the Master's Certificate?

AVC's Bootcamp helps you master in-demand skills at a faster pace and increase your marketability. Regardless of your career goals, whether you are a beginner or looking for opportunities to upgrade your skills to change careers, AVC's Bootcamp is worth the investment. These certificates are highly sought after.

Note: This Bootcamp is not equivalent to a university degree. We are not a university. This Bootcamp master's degree means that you have completed the entire program and all the essential knowledge about the subject and that you can fully “master” the subject.

What does a data scientist do?

A data scientist is someone who collects, cleans, analyzes, and visualizes large amounts of data to draw meaningful conclusions and communicate them to business leaders. This data is collected from various sources, processed into a format suitable for analysis, and fed into an analytics system where statistical analysis is performed to gain actionable insights.

Such actionable insights help solve complex business problems and make better decisions. Data scientists use data science techniques such as exploratory data analysis, statistical modeling, and machine learning to discover hidden patterns in data. If you want to pursue a career as a data scientist, this data science course can help you handle all of these responsibilities.

Who are the instructors for this course? How are they selected?

Our highly qualified data science instructors are industry experts with years of relevant experience in machine learning, Python for data science, and applied data science.

All have gone through a rigorous selection process that includes profile screening, technical evaluation, and a training demo before being certified to teach for us. We also ensure that only trainers with high alumni ratings remain on our faculty.

Why enroll in the Data Scientist Bootcamp at AVC?

Upon completion of this data science course, you will receive IBM certificates for the respective courses in the learning path. These certificates will attest to your skills and validate your data science expertise.

Additional benefits of this course include:

• Masterclasses by IBM experts
• “Ask me anything” sessions with IBM leadership
• Exclusive hackathons run by IBM
• Industry-recognized data science certification
• Live interactive sessions on the latest AI trends, such as generative AI, prompt engineering, explainable AI, and more
• Learn about ChatGPT, DALL-E, Midjourney, and other prominent tools

What are the requirements for the Data Scientist Bootcamp?

No prior experience is required to join the program. The training starts at an introductory level and progresses (step by step) to expert level. By the end of the program, you will have a comprehensive knowledge base and will be able to demonstrate your ability to apply your new knowledge in a variety of practical tasks and projects.

What is the format of the Bootcamp? Do I have to come to a training center?

The programs are entirely distance learning courses. The components are practical e-learning courses that you can complete at your own pace and at your convenience, and which you can also access from your mobile phone (our app).

There are also online classroom sessions via our advanced professional distance learning system. We have a range of time slots to choose from, and we always record the sessions so you can listen to them if you miss anything or want to review information. There is always someone on hand to help and support you if you have any questions about the skills you are learning.

When can I take Bootcamp live online courses?

The timing of each course varies for different groups. You will be given access to a dashboard with a number of different time slots for the same session/topic. You decide which date and time suits you best. Some are scheduled on weekday afternoons, while others are scheduled on weekend mornings or evenings. The schedule is based on factors such as the number of interested participants and the availability of instructors. If you miss a session, you can always watch recordings of that session. You will never miss anything!

When can I unlock my Master Certificate?

You must complete at least 85% of the course to unlock your certificate. This applies to all master programs. One of the criteria for obtaining the Master Certificate is to participate in the live courses. However, if you are unable to participate live but can watch the recordings, we can make an exception. It is important that you watch the recordings if you are unable to participate in the live sessions.

What kind of support will I receive?

We offer support via email, chat, and phone. We also have a dedicated team that provides assistance on request via our community forum. In addition, you will have lifetime access to the community forum, even after you have completed your courses with us.

Why become a data scientist?

Becoming a data scientist is lucrative yet compelling, given the robust growth of the industry. The demand for skilled data scientists exceeds supply, leading to a talent gap of 250,000 professionals by 2024.

What will be the career path after completing the Data Scientist Bootcamp?

Organizations across industries rely heavily on data-driven decision-making for competitive growth. This shift has made the role of data scientist one of the most thriving career options in the current job market. Qualified data professionals who can analyze and interpret complex data are in high demand. You can expect competitive salaries, growth opportunities, and the chance to work with cutting-edge technology.

Completing the data science course from AVC opens up several promising career paths, including positions as a data scientist, data analyst, machine learning engineer, or business intelligence analyst.

Roles such as data engineer in specialized areas such as Natural Language Processing (NLP) or computer vision are also viable options. These careers span various industries such as IT, finance, healthcare, and retail.

Can recent graduates apply for jobs after completing this Data Scientist Bootcamp?

Data scientists are in high demand today, and companies are willing to pay higher salaries for entry-level positions. However, you need to demonstrate deep data science knowledge and gain industry exposure to become a data scientist. Our data science course equips recent graduates with all the necessary skills, making them industry-ready to become successful data scientists.

This online data science program includes applied data science assignments and real-world data science projects, making it an incredible option to start your journey in data science.

Which industries use data science the most?

Data science finds applications in major industry sectors, such as healthcare, banking and finance, retail, automotive, marketing, manufacturing, and government. Industries such as technology, advertising, energy, and utilities, among others, also employ many data scientists. This data science certification course is beneficial if you want to enter any of these sectors as a professional.