Unlock your potential and step into the future—master AI today and become the innovator of tomorrow!
Attend all scheduled classes, whether online or in-person, to gain in-depth knowledge and hands-on experience. Engage actively in lectures, discussions, and practical exercises to maximize your learning outcomes.
Work on hands-on assignments and projects to apply the concepts learned in real-world scenarios. Successfully complete the capstone project, demonstrating your ability to implement AI solutions.
Take the final assessment or evaluation to showcase your skills and understanding of AI concepts. Upon successfully completing the training and evaluation, receive an AI Certification to validate your expertise and boost your career.
Learning Path
Day 1: Python Basics (1.5 Hours + 30 Minutes Introduction)
Topics Covered (1 hour):
○ Introduction to Python: Syntax, variables, and data types.
○ Control structures: Loops (for, while), conditionals (if-else).
○ Writing and using functions.
Hands-on Exercise (0.5 hours):
○ Write basic Python code and practice loops and conditionals.
Day 2: Python Data Structures (1.5 Hours)
Topics Covered (1 hour):
○ Core data structures: Lists, tuples, sets, dictionaries.
Hands-on Exercise (0.5 hours):
○ Perform operations using Python’s data structures.
Day 3: Introduction to Python Libraries (1.5 Hours)
Topics Covered (1 hour):
○ NumPy: Arrays, indexing, basic operations.
○ Pandas: DataFrames, data cleaning, and manipulation.
Hands-on Exercise (0.5 hours):
○ Load and manipulate datasets with Pandas.
○ Perform basic array operations with NumPy.
Day 4: Data Visualization (1.5 Hours)
Topics Covered (1 hour):
-
Visualizing data with Matplotlib.
-
Creating advanced plots using Seaborn.
Hands-on Exercise (0.5 hours):
-
Generate histograms, scatterplots, and line plots.
-
Visualize relationships in a dataset.
Day 5: Introduction to Machine Learning (1.5 Hours)
Topics Covered (1 hour):
○ Overview of machine learning: Supervised vs. unsupervised learning.
○ Understanding datasets: Features, labels, train-test split.
○ Introduction to the scikit-learn library.
Hands-on Exercise (0.5 hours):
○ Explore a dataset and split it into training and testing sets.
Day 6: Supervised Learning - Regression (1.5 Hours)
Topics Covered (1 hour):
○ Introduction to regression: Linear regression basics.
○ Evaluation metrics: Mean Absolute Error (MAE), R-squared.
Hands-on Exercise (0.5 hours):
○ Build and evaluate a linear regression model on a dataset.
Day 7: Supervised Learning - Classification (1.5 Hours)
Topics Covered (1 hour):
○ Introduction to classification: Logistic regression basic
○ Model evaluation: Accuracy, precision, recall, F1 score.
Hands-on Exercise (0.5 hours):
○ Implement logistic regression on a classification dataset
○ Interpret evaluation metrics.
Day 8: Introduction to Unsupervised Learning (1.5 Hours)
Topics Covered (1 hour):
○ Basics of clustering: K-Means algorithm.
○ Dimensionality reduction: Principal Component Analysis (PCA).
Hands-on Exercise (0.5 hours):
○ Perform clustering on a dataset and visualize clusters.
Day 9: Real-World Case Study (1.5 Hours)
Topics Covered (1 hour):
○ End-to-end ML pipeline: Data preprocessing, feature engineering, model
training.
○ Applying supervised and unsupervised learning techniques.
Hands-on Exercise (0.5 hours):
○ Work on a real dataset (e.g., customer segmentation or price prediction).
Day 10: Wrap-Up and Next Steps (1.5 Hours)
Topics Covered (1 hour):
Capstone Project:
○ At the end of the program, participants will complete a small project to
demonstrate their understanding of AI concepts and how to apply them.
Projects will be assessed based on creativity, technical execution, and
real-world relevance.
Q&A session for participants.
○ Provide a Roadmap document for further learning: Advanced Python, deep
learning, or NLP.
Hands-on Exercise (0.5):
○ Final project presentations and discussions. (5 min presentation for each
student)
Completion Certification
○ Participants who complete the course and capstone project will receive a
certificate of completion, which they can add to their resumes or Linked
profiles
Shaping the Future: Guiding Minds and Innovating with Excellence in AI Education!
Our AI instructors bring 5–12 years of hands-on expertise in teaching and applying advanced machine learning, data analysis, and data visualization techniques. With a proven track record of building and deploying AI models across various industries, they are passionate about simplifying complex concepts for learners. Their in-depth knowledge, combined with a practical, project-driven approach, ensures every student gains the skills needed to excel in real-world AI applications. Whether you’re a beginner or looking to advance your career, their guidance will inspire and empower your AI journey.
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TESTIMONIALS
One of the best and First Data Science services includes Tutoring in python, Data Analysis, Model Building. I am very satisfied with their services. Highly recommended.
Geeta Bajaj
Neerja is one of the best instructors I ever had.
The ability to clearly explain the concepts. Being available to help her students whenever they ask for is something I respect a lot about her.
Navnoor Kahlon
Data Analyst
I strongly recommend Neerja as an exceptional teacher of data visualization. Her ability to break down complex concepts into easy-to-understand parts made the learning experience both enjoyable and practical. I enjoyed so much being a student in her class. Her teaching style was interactive and engaging and provided opportunities for students to practice their skills through hands-on exercises and real-world examples. The knowledge I got from her is making me excel in my projects, so if you want to get a widely experienced professional don’t hesitate to contact her.
Isreal Draiz
Data Engineer
Neerja was able to explain complex ideas of Machine Learning in a way that is very easy to understand. She is also a very good communicator and knows how to get the message across in a very clear and concise manner. I would highly recommend Neerja for any Machine Learning related material.
Imran Khan
Associate Director
I wanted to take a moment to express my sincere appreciation for your outstanding work as a Data Science Instructor. Your expertise, teaching abilities, and positive attitude have made a significant impact on the team. Neerja actively embraces new responsibilities and consistently pursues opportunities to learn and develop as both a data scientist and instructor. I wholeheartedly recommend her to anyone seeking a skilled professional who is passionate about teaching and fostering growth in the field of data science. Thank you for being an invaluable asset!
Purvi
I highly recommend Neerja as a data science teacher. Her expertise in the field is evident in the way she communicates complex concepts in a clear and concise manner, making it easy for students to grasp difficult concepts. Neerja is also highly dedicated to her students and goes above and beyond to ensure they have the resources they need to succeed, whether that's providing extra help outside of class or creating engaging and relevant assignments. Overall, Neerja is an outstanding teacher who is passionate about helping her students develop the skills they need to succeed in the exciting and rapidly-evolving field of data science.
Daniel
I enthusiastically recommend Neerja for an instructional position in Data Science. Neerja has been an asset to our instructional team at Coding Dojo. She is knowledgeable, impactful, and thoughtful in her roles as instructor and teammate. She is committed to her students and provides both the technical and emotional support that leads them to success. Neerja eagerly welcomes new responsibilities and constantly seeks to learn and grow as a data scientist and instructor.
Brenda
I have had the pleasure of knowing Neerja as a colleague at Coding Dojo. Neerja is a wonderful instructor! When she initially started with Coding Dojo, one of her main focuses was to find ways to help students understand difficult concepts with ease. She tailored her lectures so that the information expressed while she was teaching would engage students and also be comprehendible by all of her students.
Also, Neerja is an amazing asset to our team. Both students and staff alike adore her. As an excellent team member, she has made contributions to the curriculum and content for the data science program. She is extremely knowledgeable in python, modeling, machine learning, time series analysis, and Tableau. Whether you are looking for an exceptional instructor or a well-rounded data scientist, Neerja will exceed your expectations!
Sherlin
I whole-heartedly recommend Neerja Jhingan for any position working on analyzing or modeling data, or teaching others to do so. I've worked with Neerja for the last year and I've found her to be pleasant, competent, caring, and coachable. She's a joy to work with and she completes assignments reliably and with quality. She also connects to her students and colleagues easily and is a benefit to the morale of our team.
Neerja's students often comment on her caring nature, the clarity with which she explains complex topics, her depth of knowledge on the topics, and her tangible devotion to their success. She is a very popular instructor with excellent KPIs.
Josh
Not only, Neerja is an enthusiastic, dedicated and highly skilled data scientist, but also a good mentor. She is actively and eagerly sharing her knowledge with the data science lovers through the YouTube channel ‘Brainy Data Science’. Her vast knowledge in the data analytics, feature engineering, machine learning algorithms helped many to implement the practical concepts over the Kaggle. Neerja’s ability to handle multiple tasks made a dramatic difference in the productivity. She would be an asset to any team and earns my highest recommendation.
Harpreet
Neerja is one of the dedicated and motivated data scientist I have ever known. Neerja is eagerly learning all the skills in the field of data science at a very quick pace. I must say about her analytics skills are out of the box. She has also proven that her explanation skills in data science field is at best. One must watch her youtube series where she is proving her skills very well.
Deepanshu
I met Neerja through an online study platform, she has always been very committed and seeks to acquire more and more knowledge and experience in the field of Data Science. I would like to recommend her hard skills, like python, and a huge data science toolkit, but also recommend her soft skills like curiosity, communication, negotiation and self-learning.
Lucas