Master Python and AI/ML Technologies at Future Finders, Mohali
You can get Python training from Future Finders to assist you to become ready for the market and get dream employment at different MNCs. A team of experts in the field with extensive training and experience developed the course content. You’ll learn a lot about Django and multithreading. In our Python course, which runs from beginner to expert, we cover data structures, file handling, and regular expressions. Anyone interested is invited to participate in our thorough course and benefit from academic
lectures and professional instructors’ hands-on, project-based training. After the course, you’ll receive a certificate attesting to your Python expertise.
Python is a well-liked and adaptable programming language that can be used for a wide range of tasks. What distinguishes Python from other languages, then? Why should you study this programming language instead of others like PHP or Ruby, for instance? Of course, how you learn Python will be unique from how others learn it. Nevertheless, Python offers a few broad benefits over certain other languages. Continue reading, especially if you are new to technology and coding. As you begin creating your first modest programme in Python, you will notice a number of its key advantages. Let’s examine the top 5 benefits of Python and see why it makes such a great tool for coding tasks.
Simple to learn
Priorities come first One of the simplest programming languages for novices to learn is Python. It is a high-level programming language, which means that its grammar is simple and resembles English quite a bit. By selecting a language that is simple to learn, you can spend less time debugging and correcting issues in your code. As a result, you’ll have more time to learn how to code and produce meaningful things. And what about that? Anyone may begin using Python. All it needs is a little patience and practice.
Accessibility to assistance
You will encounter challenges as you learn to code, but you will get beyond them! Because sometimes your code simply doesn’t do what it’s intended to, no matter how excellent you are at learning new things.
However, what should you do if you reach a dead end? When using Python for the first time, how do you learn how to address a certain issue?
Python has the benefit of being extremely well-liked throughout the world. For instance, the TIOBE Index assigns a ranking to programming languages based on the volume of results from searches. According to the most current TIOBE study, Python has been moving up the ranks. It is now the most widely used programming language globally: The top programming languages used globally, according to the TIOBE Index for December 2021 Python is the most widely used programming language globally according to the TIOBE Index (December 2021). As a result, Python is being studied and used by thousands of people worldwide. As a result, you can find a solution to your problem sooner than you think by just putting it into Google.
Vast international community
Speaking of finding assistance for your Python projects, you can frequently turn to the enormous global community for guidance and support. Python is widely used by developers, making it simple and quick to discover answers to a wide range of issues. You may connect with other like-minded students or experienced developers anywhere in the globe thanks to the language’s extensive developer community. Check to discover if there are any Python study groups in your region if you are brand-new to coding.
A work market talent that is in demand
To increase your chances of prosperous future employment, learning to code is undoubtedly something you want to do. And while money shouldn’t be your primary source of motivation, it may be a lovely little reward that keeps you going when things become tough. Let’s look at the Stack Overflow Developer Survey 2021 for information on the programming languages that developers utilise. Python ranks third among all responders and experienced developers as the most-used language worldwide (up from 4th place in 2020).
The most widely used programming languages, according to the Stack Overflow Developer Survey 2021. As a result, proportionately speaking, more developers desire to keep using Python than any other language.
Additionally, Python was the most sought-after language for the sixth consecutive year. This indicates that Python is something that developers who haven’t used yet claim they wish to learn. It remains to be seen if its popularity will cause the average income levels to decrease. As more programmers pick up the language and start seeking employment, the availability of competent labour may cause average wages to decline. But at this point, it’s reasonable to conclude that knowing Python is a strong ability that offers up new job opportunities.
Free educational tools
So now you are aware of how valuable Python is as a talent in the job market. The fact that you can learn Python programming for free online just adds to the intrigue. That is correct! There are thousands and thousands of free online lessons, books, and courses for beginners. As a result, you may acquire highly sought-after expertise without making a significant financial commitment.
Master Python programming with a focus on Artificial Intelligence and Machine Learning for real-world problem-solving.
Python Course
Build a strong foundation in Python programming.
- Python Basics
- Introduction to Python, Installation & IDEs
- Variables, Data Types, Operators
- Input/Output
- Basic control structures: if-else, loops (for, while)
- Data Structures
- Lists, Tuples, Dictionaries, Sets
- List comprehension
- String manipulation
- Functions, Lambda expressions
- OOP in Python
- Classes, Objects
- Inheritance, Encapsulation, Polymorphism
- Dunder (Magic) methods
- Exception handling
- Python Libraries Overview
- Working with files (txt, CSV)
- Overview of libraries (NumPy, pandas, matplotlib)
- Introduction to Python testing (unittest, pytest)
Learn essential data manipulation and visualization skills.
- NumPy
- Introduction to NumPy
- Arrays, Array operations
- Mathematical functions and array manipulations
- pandas
- Introduction to pandas
- DataFrames, Series
- Data Wrangling: Filtering, Sorting, Aggregations
- Data Visualization
- Introduction to Matplotlib and Seaborn
- Plotting basics (line plots, bar plots, histograms, etc.)
- Customizing plots
- Exploratory Data Analysis (EDA)
- Descriptive statistics (mean, median, mode, variance, etc.)
- Correlation, Covariance
- Data Cleaning: Handling missing data, outliers
- pandas-profiling, creating EDA reports
Understand the fundamentals of Machine Learning.
- Introduction to Machine Learning
- What is ML? Overview and types of ML (Supervised, Unsupervised, Reinforcement)
- Key concepts: Features, Labels, Training, Testing
- Steps of ML pipeline
- Supervised Learning – Regression
- Linear Regression
- Polynomial Regression
- Evaluation metrics (MAE, MSE, RMSE)
- Implementing regression using scikit-learn
- Supervised Learning – Classification
- Logistic Regression
- Decision Trees
- k-Nearest Neighbors (k-NN)
- Evaluation metrics (Accuracy, Precision, Recall, F1 Score)
- Model Validation
- Train-Test Split
- Cross-validation techniques
- Bias-Variance trade-off
Learn the basics of Deep Learning.
- Ensemble Learning
- Random Forests
- Bagging, Boosting (AdaBoost, Gradient Boosting)
- XGBoost
- Support Vector Machines (SVM)
- SVM for classification
- Kernels and the kernel trick
- Unsupervised Learning – Clustering
- K-Means clustering
- Hierarchical clustering
- DBSCAN
- Evaluating clustering performance
- Dimensionality Reduction
- Principal Component Analysis (PCA)
- t-SNE
- Feature Engineering and Feature Scaling
Learn the basics of Deep Learning.
- Introduction to Neural Networks
- What is Deep Learning? Differences between ML and DL
- Introduction to Artificial Neural Networks (ANN)
- Forward and Backward Propagation
- Training Neural Networks
- Activation functions (ReLU, Sigmoid, Tanh)
- Cost function and optimization (Gradient Descent, Adam)
- Overfitting, Regularization (Dropout, L2)
- Deep Learning with TensorFlow/Keras
- Introduction to TensorFlow and Keras
- Building a simple ANN
- Model evaluation and tuning (Learning Rate, Batch Size)
- Convolutional Neural Networks (CNN)
- Introduction to CNNs for image data
- Convolution and Pooling layers
- Building CNNs for Image Classification
Learn cutting-edge AI techniques.
- Recurrent Neural Networks (RNN)
- Introduction to RNNs for sequential data
- Long Short-Term Memory (LSTM) and Gated Recurrent Units (GRU)
- Time series forecasting using RNNs
- Natural Language Processing (NLP)
- Text preprocessing (Tokenization, Lemmatization)
- Word Embeddings (Word2Vec, GloVe)
- Text classification using RNN/CNN
- Reinforcement Learning (RL)
- What is Reinforcement Learning? Key concepts
- Q-Learning, Deep Q-Networks (DQN)
- Applications of RL (e.g., gaming, robotics)
- Model Deployment and AI Ethics
- Model deployment using Flask or FastAPI
- Introduction to MLOps and CI/CD for ML
- Ethical issues in AI: Bias, fairness, transparency
Throughout the 6 months, you’ll become familiar with:
- Python Libraries: NumPy, pandas, matplotlib, seaborn, scikit-learn
- ML Libraries: TensorFlow, Keras, PyTorch (optional)
- Deployment: Flask/FastAPI
- Other Tools: Git, Docker (for model deployment), Jupyter Notebooks
Our lives have undergone significant transformations as a result of the internet. More and more processes and activities in both large and small firms are moving online due to their reach and coverage. Just two stark instances of this growth are in the banking and communications sectors. Computers’ ease of use, however, has resulted in a sharp increase in malicious assaults on electronic hardware and software systems. Organizations are continually exposed to high levels of economic, operational, and strategic risks as a result of their growing reliance on computers and the Internet.
Therefore, it is difficult for these firms to prevent unwanted access to their systems and data. This foundation programme is designed to raise awareness among stakeholders about cyber security issues, as well as about the ideas behind cyber security and cyber ethics, to empower them to act responsibly online and take part in the rapidly changing information age society safely and securely. This Future Finders course complies with UGC guidelines that all Indian universities and institutions be required to offer a foundational course in cyber security at the undergraduate and graduate levels. The course may be utilised as a foundation course in cyber security across all Indian Universities and attempts to fill information gaps in the public about cyber security.
There will be recorded videos in the course materials that are based on the expert-designed syllabus. Everyone who has registered for the course can take it online. They can also download the videos and texts for use at a later time. Each lecture ends with a chance for students to ask any remaining questions of the lecturer, who is accessible online. Students have the opportunity to take an objective online exam after the course. The student will receive a certificate upon passing the exam attesting to their participation in the programme and their successful completion of it following the rules.
Apply here
| Python Course Fee and Duration | |||
|---|---|---|---|
| Track | Regular Track | Weekend Track | Fast Track |
| Course Duration | 150 - 180 days | 28 Weekends | 90- 120 days |
| Hours | 2 hours a day | 3 hours a day | 6+ hours a day |
| Training Mode | Live Classroom | Live Classroom | Live Classroom |
