• Life Cycle of Data Science
• Setup Anaconda
• Working with Jupyter and Spyder
• Introduction to Web Crawling
• Calling JSON API
• Fetch Data From SQL
• Convert into DataFrame
• Reading Different File Formats like csv , excel , tsv , json and raw Text
• Introduction To Data Analysis
• Introduction To Numpy
• Python List Vs Numpy Arrays
• Different Ways To Create Array In Numpy
• Handle Multi-Dimensional Array With Numpy
• Introduction To Pandas
• Data Analysis With Pandas
• Series And Data Frames
• Read CSV, Excel And Other Files With Pandas
• Exploratory Data Analysis With Pandas
• Statistical Analysis
• Mean, Median, Mode, Range, Variance, Standard Deviation
• Introduction To Data Visualization
• Plot Graphs With Matplotlib
• Plot Histograms, Bar Plot, Scatter Plot, Box Plot, Pie Charts Etc.
• 2D And 3D Plots With Matplotlib
• Introduction To Seaborn
• Making Graphs More Attractive With Seaborn
• Data Preprocessing With Pandas
• Introduction To Scikit-Learn
• Handle Missing Data
• Label Encoding, One Hot Encoding
• Feature Scaling
• Cross Validation – Data Split Techniques
• How Machine Learning Works
• Flow Of Machine Learning
• Different Types Of Machine Learning
• Difference Between Supervised And Unsupervised Learning
• Understanding Continuous And Categorical Data
• Introduction To Regression
• Simple And Multiple Linear Regression
• Gradient Descent
• Polynomial And Ridge Regression
• Making Predictive Models
• Logistic Regression
• Predicting Categorical Data
• K-Nearest Neighbors
• Introduction To OpenCV
• Face Detection And Recognition With OpenCV
• Recommendation Systems
• Support Vector Machines
• Naïve Bayes
• Decision Trees
• Clustering – K-Means And Hierarchical
• PCA, Dimensionality Reduction
• Introduction To NLP
• Installing NLTK
• How NLP Works
• Word And Sentence Tokenizer
• Count Vectorizer
• Text Classification With Naïve Bayes
• Spam Classification Case Study
• Sentiment Analysis
The Machine Learning with Python course is designed to provide you with a comprehensive understanding of the fundamental concepts and practical techniques used in machine learning.
Through a combination of theoretical explanations and hands-on coding exercises, this course aims to equip you with the necessary skills to build and deploy machine learning models using the Python programming language.
Develop a solid understanding of the Unity game development engine and its core features.
Learn to create interactive and visually appealing games using Unity's tools and components.
Gain proficiency in game physics, scripting, and implementing game mechanics.
Understand the process of designing game levels and user interfaces for optimal player experience.
Hello everyone, I am Ravikant Tyagi and I do have experience of 8+ years in IT as a developer and trainer. I have more than 100 websites live on internet and I have taught thousands of students, teachers & developers to learn to code and how to become professional developer with 100% practical knowledge.
Teaching Assistant having a total of 6 months of experience in teaching IT professionals. So far I have successfully deliverd 15+ trainings at various tech companies/colleges
What People Says About us
• Yes! You can attend a One Demo class free of Cost.
• All Classes sessions are recorded in HD Quality , so if you miss a class so you can watch the recordings.
• 100 % Placement Assistance.
• All our Trainers are Software Professionals, Having 7 to 15 Years’ of Experience. All Trainers worked with Top Brands.
• Feel free to contact us on :7042434524 01145138947