AI Engineer Roadmap 2025 | AI Engineer Roadmap For Beginners | AI Engineer Career Path | Simplilearn

Nov 29, 20240 likes190 views

In this video by Simplilearn, we’ve crafted a comprehensive AI Engineer roadmap, breaking down each stage to make your learning journey clear and achievable. Starting with foundational skills and getting familiar with key tools, we dive into learning Python and data structures, followed by database management, data manipulation, and essential mathematics. We then cover data analysis and core machine learning concepts before moving on to deployment, specialization, and advanced topics. Finally, we explore the importance of specialization, networking, and community engagement. Organized by months and weeks, this roadmap is designed to make becoming an AI Engineer manageable, structured, and exciting!

AI Engineer Roadmap 2025 | AI Engineer Roadmap For Beginners | AI Engineer Career Path | Simplilearn

Month 1 - Building Foundations and Getting
Started
Week 1 - 2 Computer Science Fundamentals
Bits and Bytes
Computer Networks
Programming Logic

Python Basics
Week 3 - 4
Syntax, Control Structures,
Functions
Month 2 - Learning Python and Data Structures
Data Structures
Week 5 - 6
Arrays, Linked lists, Stacks,
Queues, Trees

Week 7 - 8 SQL and Databases
Manage, Query Relational
Databases
Month 3 - Database Management, Data
Manipulation, and Mathematics
Week 9 - 10 Data Manipulation with Numpy and Pandas
Handle Large Datasets, Perform
complex operations

Week 11 - 12 Math and Statistics for AI
Linear algebra, Probability,
Calculus, Statistics
Month 3 - Database Management, Data
Manipulation, and Mathematics

Week 13 – 14 Exploratory Data Analysis (EDA)
Practice EDA by working with
real datasets from Kaggle
Month 4 - Data Analysis and Core Machine
Learning
Week 15 - 18 Machine Learning Fundamentals
Linear regression, Classification,
clustering, Decision trees

Week 19 – 20 MLOps Basics
Docker, FastAPI, and
Kubernetes
Month 5 - Deployment, Specialization, and
Advanced Topics
Week 21 - 22 Portfolio Projects
Projects on Regression and
Classification

Week 23 - 24 Introduction to Deep Learning
Neural networks, CNNs, RNNs,
Deep learning architectures
Month 5 - Deployment, Specialization, and
Advanced Topics

Week 25 – 26 Specialization in NLP or Computer Vision
Sentiment Analysis for NLP,
object detection for CV
Month 6 - Specialization, Networking, and
Community Engagement
Week 27 - 28 Mastering LangChain and LLMs
Projects on Regression and
Classification

Week 29 - 32 Professional Networking and Soft Skills
Enhance your visibility in the
field, Establish relationships
Month 6 - Specialization, Networking, and
Community Engagement

In this video on Machine Learning Roadmap 2025 from Simplilearn, we’ll guide you through the essential skills, tools, and topics to master ML in 2025, whether you're just starting out or looking to advance your career in data science. We’ll cover foundational skills, including math, statistics, and key programming languages like Python, and dive into critical ML algorithms, deep learning, NLP, and computer vision—skills in high demand for future AI projects. Plus, we’ll explore MLOps techniques for deploying and maintaining models in production, and review top frameworks like TensorFlow, PyTorch, and scikit-learn. Don’t forget to like, subscribe, and join the discussion in the comments to connect with others on this learning journey.

Data Science & Big Data - Theory.pdfRAKESHG79

This document outlines the curriculum for the course "Elective Theory II - Data Science and Big Data" for the VI semester of the Diploma in Computer Engineering program. The course covers 5 units over 80 hours on data science fundamentals, data modeling, and big data concepts including storage and processing. The objectives are to understand data science techniques, apply data analysis in Python and Excel, learn about big data characteristics and technologies like Hadoop, and explore applications of big data. Topics include linear regression, classification models, MapReduce, and using big data in fields such as marketing, healthcare, and advertising.

Big Data Analytics-Module-1 for vtu syllabus.pptxshilpabl1803

Transition From Mechanical Engineering to Data Science | Tutort AcademyTutort Academy

Python tool to data analysis and artificial intelligenceMd Aksam VK

This document provides an overview of Python tools for data analysis and artificial intelligence. It discusses various data types and structures in Python like lists, tuples, and dictionaries. It also covers data exploration techniques including reading files, handling different variable types, and data visualization. Machine learning algorithms like label encoding, logistic regression, naive bayes classification, k-means clustering, and support vector machines are explained. Code files with examples of implementing these techniques in Python are referenced.

Building Data ScientistsMitch Sanders

BDAModule-1.pptxbharathmadival8055

This document outlines the syllabus for a course on Big Data Analytics. It includes 5 modules that cover topics such as introduction to Hadoop, MapReduce and machine learning algorithms for big data. The syllabus provides learning objectives, textbook references, module outlines and topics to be covered in each module. It also specifies course outcomes, question paper pattern and module overviews that give concise descriptions of the key concepts covered in each topic.

Cse 8th sem syllabusAkshatha Nair

This document outlines the course objectives and modules for a course on Internet of Things Technology. The course aims to enable students to assess IoT applications and architectures, illustrate methods to deploy smart objects, compare application protocols for IoT, and identify the role of data analytics and security in IoT. The five modules cover topics like IoT architectures and networks, connecting smart objects, application protocols, data analytics, security, and hands-on experience with devices like Arduino and Raspberry Pi. The course outcomes are for students to interpret IoT challenges and models, compare deployment technologies, appraise protocols, and illustrate applications of IoT in industry.

Master Program in Computer Science with specialization in Data ScienceOleksii Molchanovskyi

Course outlineSumbalImran2

This course provides an introduction to data science, its applications, and the tools used. Students will learn Python, NumPy, Pandas, and scikit-learn for data analysis and machine learning. The course aims to help students understand how data science can improve emergency response, environmental impact analysis, and personalized customer services. Students will learn to find datasets, analyze data to answer research questions, and present findings. Assessment includes midterm, final exams, quizzes, assignments, and a project.

Modern Database Systems - Lecture 00Michael Mathioudakis

This document provides an overview of the Modern Database Systems course. It introduces database management systems (DBMS) and discusses why they are used and important to study. The course will cover relational database systems, semi-structured data, unstructured text, big data platforms, and graph databases. Assignments will include pen and paper problems and programming assignments using tools like MySQL, MongoDB, and Spark. The document outlines the syllabus, logistics, workload, and credits sources for some slides.

Datascience syllabus covers datascience topicsDurgaDeviP2

PDS Unit - 1 Introdiction to DS.pptssuser52a19e

This document provides an introduction to a course on Python for Data Science. It discusses key concepts related to data, information, databases, data warehouses, big data, and data science. It outlines the course objectives, which are to train students to solve computational problems using Python and build different types of models. The syllabus covers topics like introduction to data science, NumPy, data manipulation with Python, data cleaning/preparation/visualization, and machine learning using Python. Textbooks and reference materials are also listed.

2016 Chapter 2 - Intro. to Data Sciences.pptxmussie143tadesse

Lecture_1_Intro.pdfpaijitk

This document provides an overview of the CS639: Data Management for Data Science course. It discusses that data science is becoming increasingly important as more fields utilize data-driven approaches. The course will teach students the basics of managing and analyzing data to obtain useful insights. It will cover topics like data storage, predictive analytics, data integration, and communicating findings. The goal is for students to learn fundamental concepts and design data science workflows and pipelines. The course will include lectures, programming assignments, a midterm, and final exam.

Lecture1 introduction to big datahktripathy

This document provides a syllabus for a course on big data. The course introduces students to big data concepts like characteristics of data, structured and unstructured data sources, and big data platforms and tools. Students will learn data analysis using R software, big data technologies like Hadoop and MapReduce, mining techniques for frequent patterns and clustering, and analytical frameworks and visualization tools. The goal is for students to be able to identify domains suitable for big data analytics, perform data analysis in R, use Hadoop and MapReduce, apply big data to problems, and suggest ways to use big data to increase business outcomes.

Data science presentationMSDEVMTL

This document provides an overview of getting started with data science using Python. It discusses what data science is, why it is in high demand, and the typical skills and backgrounds of data scientists. It then covers popular Python libraries for data science like NumPy, Pandas, Scikit-Learn, TensorFlow, and Keras. Common data science steps are outlined including data gathering, preparation, exploration, model building, validation, and deployment. Example applications and case studies are discussed along with resources for learning including podcasts, websites, communities, books, and TV shows.

A Comprehensive Learning Path to Become a Data Science 2021.pptxRajSingh512965

The 2021 data science learning path provides a comprehensive curriculum to become a data scientist. It includes extended skills in storytelling, model deployment, unsupervised learning, exercises, and projects. The path covers key skills and tools like Python, R, machine learning algorithms, deep learning, natural language processing, and model deployment. It consists of monthly modules that progress from the data science toolkit to advanced topics, with hands-on training and real-world projects.

Informatics_Practices_SrSec_2024-25.pdf.vmkvibha1

Mastering in Data Science 3RITPL-1 (1).pdftarunprajapati0t

This document provides information about a Mastering in Data Science training program powered by 3RI Technologies. It offers advanced industry-oriented courses in data science, machine learning, and Python taught by experienced faculty. The curriculum is designed by industry experts and includes real-world projects and case studies. The training aims to help professionals develop hands-on skills and become technically proficient through teaching assistance and support.

This is ChatGPT Book Data Science Roadmap.pdfimransahito82

MTECH IT syllabusVijayananda Mohire

This document outlines the syllabus for a Masters of Technology in Information Technology (M.Tech-IT) program over 4 semesters. It includes 16 courses covering topics like interactive computer graphics, algorithm analysis and design, advanced computer architecture, advanced DBMS, object oriented software engineering with UML, AI and neural networks, and elective subjects in areas like automata, parallel computing, embedded systems and more. Students must complete 16 credits per semester for a total of 64 credits to earn the M.Tech-IT degree. The syllabus provides detailed descriptions of the topics to be covered in each course.

Das patrac sandpythonwithpracticalcbse11NumraHashmi

The document is a textbook on computer science and Python programming for CBSE Class XI. It covers the theory and practical syllabus prescribed by CBSE. The textbook is divided into five parts - Computer Systems and Organisation, Computational Thinking and Programming, Data Management, Society Law and Ethics, and solutions to programming exercises. It includes chapters on topics like computer hardware, Python programming concepts, SQL, NoSQL and cyber safety. Each chapter provides learning objectives, concepts, examples, questions and programming assignments. The textbook aims to help students learn computer science concepts and develop Python and database programming skills as per the CBSE Class XI syllabus.

M.tech cse 10july13 (1)vijay707070

This document outlines the curriculum for a Master of Technology (Computer Science and Engineering) degree program. It includes the course requirements and electives for each of the four semesters. In the first semester, students will take courses in mathematical foundations, computer architecture, data structures and algorithms, computer networks, and research methodology. They will also complete labs in network management and a term paper. The subsequent semesters include additional theory courses, labs, and electives in areas such as databases, distributed systems, software engineering, and a capstone project. The degree requires a total of 75 credits over four semesters.

K.sabitha NM.pptx advance data science with pythonksaravanakumar450

Syllabus.pdfarvind pandey

The document provides details about an advanced database management systems course including its objectives, course contents, and requirements. The course aims to study advanced database techniques beyond fundamental concepts. It contains 5 units covering relational and object-oriented database models, emerging technologies like data warehousing and data mining, and database standards. Students must complete a project using a commercial object-oriented database management system and model-view-controller framework.

Radhika (30323U09065).pptx data science with pythonksaravanakumar450

VTU technical seminar 8Th Sem on Scikit-learnAmarnathKambale

Top 50 Scrum Master Interview Questions | Scrum Master Interview Questions & ...Simplilearn

This Simplilearn video on Cyber Security Interview Questions and Answers for 2025 introduces you to the most commonly asked questions in cyber security interviews, along with their detailed answers. Covering key topics such as Networking, Software and Programming, Operating Systems and Applications, Cyberattacks, and Cryptography, this video serves as a valuable resource for your cyber security interview preparation.

Bagging Vs Boosting In Machine Learning | Ensemble Learning In Machine Learni...Simplilearn

In this video by Simplilearn, we will walk you through bagging and boosting, the two main types of Ensemble Learning. We start by explaining what Ensemble Learning is with a simple example. Then, we discuss bagging, its implementation steps, and its benefits in improving model accuracy. Next, we explore boosting, the steps involved, and its key advantages. Finally, we compare bagging and boosting to highlight their differences. By the end of this video, you will understand how these methods enhance machine learning models and when to use each technique. Bagging and boosting are ensemble learning techniques that improve model accuracy. Bagging trains multiple models on random data subsets and combines their predictions, reducing variance and preventing overfitting . Boosting trains models sequentially, correcting previous errors to reduce bias and enhance accuracy

More Related Content

Similar to AI Engineer Roadmap 2025 | AI Engineer Roadmap For Beginners | AI Engineer Career Path | Simplilearn (20)

Master Program in Computer Science with specialization in Data ScienceOleksii Molchanovskyi

Course outlineSumbalImran2

Modern Database Systems - Lecture 00Michael Mathioudakis

Datascience syllabus covers datascience topicsDurgaDeviP2

PDS Unit - 1 Introdiction to DS.pptssuser52a19e

2016 Chapter 2 - Intro. to Data Sciences.pptxmussie143tadesse

Lecture_1_Intro.pdfpaijitk

Lecture1 introduction to big datahktripathy

Data science presentationMSDEVMTL

A Comprehensive Learning Path to Become a Data Science 2021.pptxRajSingh512965

Informatics_Practices_SrSec_2024-25.pdf.vmkvibha1

Mastering in Data Science 3RITPL-1 (1).pdftarunprajapati0t

This is ChatGPT Book Data Science Roadmap.pdfimransahito82

MTECH IT syllabusVijayananda Mohire

Das patrac sandpythonwithpracticalcbse11NumraHashmi

M.tech cse 10july13 (1)vijay707070

K.sabitha NM.pptx advance data science with pythonksaravanakumar450

Syllabus.pdfarvind pandey

Radhika (30323U09065).pptx data science with pythonksaravanakumar450

VTU technical seminar 8Th Sem on Scikit-learnAmarnathKambale

Master Program in Computer Science with specialization in Data ScienceOleksii Molchanovskyi

Course outlineSumbalImran2

Modern Database Systems - Lecture 00Michael Mathioudakis

Datascience syllabus covers datascience topicsDurgaDeviP2

PDS Unit - 1 Introdiction to DS.pptssuser52a19e

2016 Chapter 2 - Intro. to Data Sciences.pptxmussie143tadesse

Lecture_1_Intro.pdfpaijitk

Lecture1 introduction to big datahktripathy

Data science presentationMSDEVMTL

A Comprehensive Learning Path to Become a Data Science 2021.pptxRajSingh512965

Informatics_Practices_SrSec_2024-25.pdf.vmkvibha1

Mastering in Data Science 3RITPL-1 (1).pdftarunprajapati0t

This is ChatGPT Book Data Science Roadmap.pdfimransahito82

MTECH IT syllabusVijayananda Mohire

Das patrac sandpythonwithpracticalcbse11NumraHashmi

M.tech cse 10july13 (1)vijay707070

K.sabitha NM.pptx advance data science with pythonksaravanakumar450

Syllabus.pdfarvind pandey

Radhika (30323U09065).pptx data science with pythonksaravanakumar450

VTU technical seminar 8Th Sem on Scikit-learnAmarnathKambale

More from Simplilearn (20)

Top 50 Scrum Master Interview Questions | Scrum Master Interview Questions & ...Simplilearn

Bagging Vs Boosting In Machine Learning | Ensemble Learning In Machine Learni...Simplilearn

Future Of Social Media | Social Media Trends and Strategies 2025 | Instagram ...Simplilearn

In this video "Future of Social Media" we’ll talk about how social media is changing and shaping our future. You’ll learn about Facebook’s exciting plans for the Metaverse, TikTok’s influence on trends and shopping, and how platforms like Instagram are evolving into powerful marketing and e-commerce tools. We’ll also explore new platforms like BlueSky and BeReal that focus on privacy and authenticity, and how social media is becoming the go-to place for searching and customer service. By the end of this video, you’ll understand the major trends, challenges, and opportunities in social media and how they’re impacting the way we connect, shop, and interact every day.

SQL Query Optimization | SQL Query Optimization Techniques | SQL Basics | SQL...Simplilearn

In this video, we’ll explore 12 best practices for SQL query optimization to help you write faster, more efficient queries that improve database performance. SQL is the backbone of data management, but poorly optimized queries can slow down servers, increase load times, and waste resources. We'll start by understanding why SQL optimization is important with a simple example—retrieving customer details. A poorly written query pulls unnecessary data, making it slow and resource-heavy, while an optimized query fetches only what’s needed, improving speed and efficiency. You’ll learn practical techniques like using indexes effectively, avoiding SELECT to fetch only the required columns, optimizing JOIN operations, minimizing subqueries, and leveraging stored procedures for better performance. These best practices will ensure your queries run lightning fast while keeping your database efficient.By the end of this video, you’ll have the skills to optimize your SQL queries and improve overall database performance. Like, subscribe, and drop a comment with your biggest SQL takeaway—let’s optimize those queries together!

SQL INterview Questions .pTop 45 SQL Interview Questions And Answers In 2025 ...Simplilearn

In this video, we cover the Top 45 SQL Interview Questions in 2025, designed to help both freshers and experienced professionals prepare for their next big interview. These questions range from the basics, such as understanding SQL commands like SELECT, INSERT, and DELETE, to more advanced topics like joins, normalization, indexing, and transaction management. We also dive into real-world scenarios, such as handling SQL injection, using triggers, and explaining the ACID properties for database reliability.

How To Start Influencer Marketing Business | Influencer Marketing For Beginne...Simplilearn

In this video, we’ll show you How to Start an Influencer Marketing Business in 2025 and turn this booming trend into your next big venture. Influencer marketing isn’t just about flashy endorsements—it’s about building trust, authentic connections, and impactful storytelling. We’ll start by explaining influencer marketing and why it works so well, with examples like Cristiano Ronaldo’s Nike partnership and Selena Gomez’s Rare Beauty campaign. You’ll learn about the four types of influencers—mega, macro, micro, and nano—and how to choose the right one for your goals. Next, we’ll guide you through creating a winning strategy, including finding influencers, setting budgets, defining goals, and crafting briefs that deliver results. Plus, we’ll highlight common pitfalls to avoid and how to measure success using tools like Google Analytics.

Cyber Security Roadmap 2025 | How To Become Cyber Security Engineer In 2025 |...Simplilearn

In this video by Simplilearn, we’ll take you through the Cybersecurity Engineer Roadmap for 2025 step by step! Learn about the increasing demand for cybersecurity professionals, which companies are hiring, the salaries you can expect, and what a Cybersecurity Engineer does. We’ll explain their key roles, responsibilities, and the technical and soft skills you need to succeed. Plus, we’ve created a detailed weekly roadmap with daily goals to help you go from having no experience to landing your first cybersecurity job in 2025. Whether you’re a beginner or switching careers, this video is your complete guide to starting a successful journey in cybersecurity!

How To Become An AI And ML Engineer In 2025 | AI Engineer Roadmap | AI ML Car...Simplilearn

In this Simplilearn video, we bring you a complete step-by-step guide to becoming an AI and ML Engineer in just 12 weeks! Whether you're starting from scratch or brushing up your skills, this roadmap has you covered. We’ll begin with the basics of AI and Python programming, then move on to advanced topics like LangChain, large language models (LLMs), and practical applications of AI and ML. Along the way, you’ll learn how to build an impressive resume, create a standout portfolio, and master networking strategies to land your dream job. If you’re aiming to kickstart your career as an AI and ML Engineer in 2025, this video is packed with all the knowledge and tools you need!

What Is GitHub Copilot? | How To Use GitHub Copilot? | How does GitHub Copilo...Simplilearn

In this Simplilearn video, I dive into one of the most talked-about tools in tech—GitHub Copilot! You'll discover what GitHub Copilot is, how it works, its game-changing features that are transforming the way we code, and the challenges developers face while using it. Plus, we’ll explore how AI-powered tools like this are shaping the future of software development. Whether you're a coding enthusiast or a seasoned developer, this video breaks it all down in a simple and engaging way. Hit play and see how GitHub Copilot can revolutionize your coding journey!

Top 10 Data Analyst Certification For 2025 | Best Data Analyst Certification ...Simplilearn

In this video by Simplilearn, I’ll walk you through the expanding scope and financial growth of Data Analytics worldwide, illustrating why pursuing a Data Analytics Certification is essential for advancing in this high-demand field. We'll cover the incredible opportunities that data analytics offers across industries, making it a valuable skill set with impressive salary potential. Finally, I'll dive into the Top 10 Data Analytics certifications that can boost your career, enhance your skills, and increase your earning potential. Whether you’re starting or looking to advance, this guide will help you choose the right certification to achieve your career goals in data analytics.

Complete Data Science Roadmap For 2025 | Data Scientist Roadmap For Beginners...Simplilearn

In this Simplilearn video, we outline the key roadmap to stand out in the data science field by 2025! From mastering core programming languages like Python and using version control tools like Git to understanding essential data structures, algorithms, and SQL—this guide has it all. We dive into crucial math and stats areas such as calculus, linear algebra, and probability, as well as data preprocessing and visualization with Numpy, Pandas, Matplotlib, and Seaborn. Gain insights into machine learning fundamentals like supervised and unsupervised learning, plus key tools, deep learning concepts, and specializations in NLP, Computer Vision, and Big Data. This guide will give you all the skills to succeed as a top data scientist!

Top 7 High Paying AI Certifications Courses For 2025 | Best AI Certifications...Simplilearn

Data Cleaning In Data Mining | Step by Step Data Cleaning Process | Data Clea...Simplilearn

In this comprehensive video by Simplilearn, we dive into the essential process of data cleaning in data mining. We start with a brief overview of data mining, exploring how it helps businesses uncover valuable insights from large datasets. Then, we move into the heart of the topic, explaining what data cleaning is and why it's a critical step in ensuring accurate and reliable data analysis. You'll learn about the steps involved in data cleaning, from removing duplicates and handling missing data to standardizing formats and correcting errors. Finally, we introduce the top 6 tools for data cleaning, showcasing how each tool can streamline the process and improve data quality for better decision-making. Whether you're a data enthusiast or a professional looking to sharpen your skills, this video will provide valuable insights into mastering data cleaning techniques for effective data mining.

Top 10 Data Analyst Projects For 2025 | Data Analyst Projects | Data Analysis...Simplilearn

In this video, "Top 10 Data Analyst Projects for 2025" from Simplilearn, we dive into the most impactful and trending projects every aspiring and seasoned data analyst should consider. We will guide you through what each project entails, its relevance in the industry, and provide step-by-step instructions on how to get started—from data collection and cleaning to visualization and drawing actionable insights. Whether you’re looking to impress in job interviews, transition into a new role, or simply expand your data skill set, these projects are perfect for keeping you ahead in 2025.

Kotter's 8-Step Change Model Explained | Kotter's Change Management Model | S...Simplilearn

In this video on Kotter's 8-Step Change Model Explained from Simplilearn, we explore Kotter's 8-Step Change Model, a widely-used framework for effective change management created by Dr. John Kotter. This model outlines a step-by-step approach to successfully guide organizations through change, from creating a sense of urgency and forming a powerful coalition to building on short-term wins and anchoring new approaches in the culture. Whether you're a leader, manager, or just interested in understanding how to navigate change, this video provides a clear and concise overview of each step, offering practical insights to ensure successful and lasting transformation. Don't forget to like, subscribe, and share for more videos.

Gen AI Engineer Roadmap For 2025 | How To Become Gen AI Engineer In 2025 | Si...Simplilearn

In this video by Simplilearn, we’ll guide you through the Generative AI Engineer Roadmap for 2025. Generative AI, a technology that creates text, images, music, and more, is transforming industries like healthcare, finance, and entertainment. We’ll cover what Generative AI is, what a Generative AI Engineer does, and the skills you need, including Python programming, machine learning, and advanced topics like Prompt Engineering. Plus, learn about career opportunities, expected salaries, and resources like Simplilearn’s PostGraduate Program in AI and Machine Learning to kickstart your journey. Following are the topics covered in this video.

Top 10 Data Analyst Certification For 2025 | Best Data Analyst Certification ...Simplilearn

Complete Data Science Roadmap For 2025 | Data Scientist Roadmap For Beginners...Simplilearn

Top 7 High Paying AI Certifications Courses For 2025 | Best AI Certifications...Simplilearn

In this Simplilearn video, I’ll be guiding you through the future trends in AI, exploring how they’re transforming industries across the globe—from healthcare and finance to retail and logistics. We’ll discuss why pursuing an AI certification has become essential in today's fast-evolving tech landscape, providing you with the skills and knowledge that employers are actively seeking. Finally, I’ll walk you through the Top 7 AI certifications that can supercharge your career, covering everything from machine learning foundations to specialized AI skills in areas like deep learning, NLP, and big data analytics.Whether you're just starting your journey in tech, passionate about AI, or an experienced professional aiming to expand your skill set, these certifications provide a structured pathway to gain in-demand expertise, positioning you for cutting-edge roles and career advancement.

What Is ETL (Extract, Transform, Load)? | ETL Tools | ETL Tutorial | ETL Proc...Simplilearn